JP4868990B2 - Closed loop automatic recognition device and closed loop automatic recognition method - Google Patents

Description

  The present invention relates to a closed-loop automatic recognition apparatus, a closed-loop automatic recognition method, and a program for recognizing a closed loop composed of a plurality of segments represented by line segments, arcs, and segmented curves.

  When a user draws a cross-sectional shape of a member using a CAD system or an analysis pre-post, the member is often expressed using a plurality of segments such as line segments, arcs, segmented spline curves, and the like. . The same applies to the case where the sectional shape of the member output from the CAD system is taken into another CAD system or an analysis pre-post. Conventionally, as a method for recognizing the plurality of segments as a closed loop of one member, a method for selecting and specifying all the segments one by one with a mouse pointer, or an inclusion specification in a shape such as a BOX or a circle. There is a way.

  Patent Document 1 describes a method for automatically searching for a boundary (closed loop). In this method, first, a segment specified by the user or a segment closest to the position specified by the user is used as a search start segment, and an angle formed by a plurality of intersecting next segment selection candidates is obtained. Next, the next segment is selected according to the angle condition, the segment search is sequentially repeated, and the search is terminated when the search start segment is reached.

  Another method for automatically searching for a boundary (closed loop) is described in Patent Document 1. In this method, for a plurality of next segment selection candidates that intersect, the segment search target is limited or switched depending on the type of segment such as a line segment, an arc, or a segmented spline curve, and display or non-display. .

JP-A-3-22182 JP 7-121598 A

  However, in the method in which the user selects all the segments one by one with the mouse pointer, there are cases where selection is made by mistake when segments constituting a plurality of members overlap. There is also a problem that it takes a huge amount of time when the number of segments is large. In addition, in the method of comprehensively specifying a shape such as a BOX or a circle, when a segment constituting a plurality of members overlaps, a segment other than the target segment may be selected. For this reason, there is a problem that it is difficult to specify a desired closed region. Even in the above-described method for automatically searching for a boundary (closed loop), when segments of a plurality of members are overlapped, a segment constituting one member may be erroneously searched.

  Furthermore, as a result of the user creating the cross-sectional shape of the member with a CAD system or an analytical pre-post, a plurality of segments such as line segments, arcs, segmented spline curves, and the like are not necessarily matched or intersected. Is not limited. The same applies to the case where the sectional shape of the member output from the CAD system is taken into another CAD system or an analysis pre-post. Furthermore, in either case, the endpoints may even be slightly separated. In such a situation, the continuity of the segment itself cannot be secured and the closed loop itself cannot be formed by the designation method using the mouse pointer, the comprehensive designation method using the shape such as BOX or circle, and the automatic boundary search method. There is a problem.

  An object of the present invention is to provide a closed-loop automatic recognition apparatus, a closed-loop automatic recognition method, and a program capable of easily and reliably recognizing a closed loop composed of a plurality of segments including a line segment, an arc, a segmented curve, and the like. Is to provide.

  As a result of intensive studies to solve the above problems, the present inventor has come up with various aspects of the invention described below.

A closed-loop automatic recognition apparatus according to the present invention is a closed-loop automatic recognition apparatus that recognizes a closed loop configured by combining a plurality of segments each represented by a line, and includes a user's operation for one of the plurality of segments. Input means for inputting a specification; tolerance value input means for inputting a tolerance value regarding the distance between the end points of adjacent segments that can be permitted in recognition of the closed loop; and the tolerance value from one end point of the specified segment. A first extracting means for extracting other end points in the range; and an end point of another segment within the allowable range from the other end point of the segment including the end point extracted by the first end point extracting means. A second extracting means for extracting, and a segment including the end point extracted by the second extracting means is designated by the input means. An identification means for identifying a group of a plurality of segments including the end points extracted so far as a closed loop, and a highlighting means for highlighting the closed loop identified by the identification means, The second extracting means includes the end point extracted by the first extracting means until the segment including the extracted end point matches the segment designated via the input means. deemed to, to repeat the extraction end point of the other segments, the first extracting means, if the segment containing the endpoints of the range of the allowable value exists 2 or more, any from among the two or more segments 1 segment is selected and the extraction is continued. Even if the extraction by the second extraction means is performed a predetermined number of times, the input means is used. If the selected segment does not match the selected segment, it is determined that the selection is incorrect, and another one of the two or more segments is selected, and then extraction by the second extraction unit is continued. characterized in that it.

A closed-loop automatic recognition method according to the present invention is a closed-loop automatic recognition method for recognizing a closed loop configured by combining a plurality of segments each represented by a line, and a user's operation with respect to one of the plurality of segments. An input step of inputting a specification, a tolerance input step of inputting a tolerance regarding the distance between the end points of adjacent segments that can be permitted in the recognition of the closed loop, and an allowable value from one end point of the specified segment. A first extracting step for extracting other end points in the range, and extracting the end points of other segments within the tolerance range from the other end point of the segment including the end points extracted in the first end point extracting step And a segment including the end points extracted in the second extraction step is the input. When matching with the segment specified in the step, a specific step of specifying a group of a plurality of segments including the end points extracted so far as a closed loop, a highlighting step of highlighting the closed loop specified in the specific step, And the second extraction step extracts the end points extracted in the second extraction step until the segment including the extracted end points matches the segment specified in the input step. is regarded as the extracted end point in step have a step of repeating the extraction of the end point of another segment, the first extraction step, if the segment containing the endpoints of the range of the allowable value exists 2 or more, the The above extraction is performed after arbitrarily selecting one segment from two or more segments. Subsequently, when the extraction in the second extraction step does not coincide with the segment designated through the input means even if the extraction is performed a predetermined number of times, the selection is incorrect. in it selects another first segment of the two or more segments, characterized in that it have the step of re-continue the extraction of the second extraction steps.

A program according to the present invention causes a computer to execute each means of the above closed loop automatic recognition apparatus .

  According to the present invention, as long as a user designates one segment, automatic recognition of a closed loop composed of a plurality of segments constituting one member is easily and reliably performed. Therefore, setting of members in a CAD system, an analysis pre-post, or the like is facilitated.

  Hereinafter, embodiments of the present invention will be specifically described with reference to the accompanying drawings.

(First embodiment)
First, a first embodiment of the present invention will be described. FIG. 1 is a block diagram showing a configuration of a closed-loop automatic recognition apparatus according to the first embodiment of the present invention.

  When a user creates a cross-sectional shape of a member using a CAD system or an analysis pre-post, a member cross-section composed of a plurality of segments is created and displayed on the display device 12. When reading the sectional shape data of the member once outputted, when the data stored in the hard disk 8 is designated and called by the input device 10, it is displayed on the display device 12. The segment displayed here is composed of a line and two end points at both ends thereof. Examples of the line type include a line segment, an arc, a segmented curve, and a line connecting these.

  Then, each segment, end point information belonging to the segment, and end point coordinates are stored in the hard disk 8. Subsequently, when one of the segments constituting the closed loop to be defined is designated by the input device 10, the closed loop automatic recognition processing is performed by the CPU 11, and the information being processed is stored in the hard disk 8 or the memory 9. When the processing is completed, the display color of the segments constituting the automatically recognized closed loop is changed and displayed on the display device 12.

  Next, the operation of the closed loop automatic recognition apparatus configured as described above, that is, the closed loop automatic recognition method will be described. FIG. 2 is a flowchart showing the closed-loop automatic recognition method in the first embodiment.

  First, in step S 1, each segment displayed on the display device 12, end point information belonging to these segments, and coordinates of these end points are stored in the hard disk 8.

  Next, in step S <b> 2, the user is requested to designate one of the segments constituting the closed loop to be defined from the segments displayed on the display device 12 via the input device 10.

  Next, in step S3, it is determined whether or not there is designation from the user. When designation is input, in step S4, a member number of a member to which the designated segment belongs is newly defined.

  Thereafter, in step S5, the member number defined in step S4 and the segment number of the segment specified by the user are stored in the hard disk 8.

  Subsequently, in step S <b> 6, the user is requested to set, via the input device 10, an allowable value for searching for a nearby end point from the end points constituting the segment. This setting is performed, for example, when the user inputs a numerical value in the command column 14 of FIG.

  Next, in step S7, it is determined whether there is a setting from the user. When an allowable value is input, referring to the input allowable value, an end point located in the vicinity of one end point of the specified segment is determined. The extracted information (including coordinates) is stored in the hard disk 8. Specifically, the end points located in the square region centered on the one end point and having the length of each side twice the allowable value are extracted.

  Instead of allowing the user to input an allowable value for each process, the allowable value may be stored in the hard disk 8 in advance, and the allowable value may be read instead of the processes in steps S6 and S7. In this case, as a value stored in advance, it is desirable to use a value as small as two or three digits with respect to the length of the segment constituting the member. Even when the user inputs a value in steps S6 to S7, it is desirable to input a value that is two or three digits smaller than the length of the segment that forms the member that is to form the closed loop.

  After the end points are extracted in step S8, the segment numbers of the segments including the extracted end points are stored in the hard disk 8 in step S9.

  Next, in step S10, it is determined whether the segment including the extracted end point is a segment specified by the user in steps S2 to S3. If the segment is designated by the user, a closed loop is formed. Therefore, in step S12, the segment constituting the closed loop is highlighted, and the process ends.

  On the other hand, if the segment is not a segment designated by the user, in step S11, an end point located in the vicinity of the other end point of the segment is extracted, and the information (including coordinates) is stored in the hard disk 8. The extraction criteria at this time are the same as in step S8.

  And the process of step S9-S11 is performed until the segment designated by the user in step S10 is extracted.

  Here, an example of a diagram including a plurality of segments (a diagram of sensor triggers in the paper conveyance support system) will be described, and automatic closed loop recognition performed on the diagram will be described. Here, it is assumed that the image shown in FIG. 3 is displayed on the display device 12 as a result of reading the CAD data including the sensor trigger data of the paper conveyance support system. That is, it is assumed that the sensor trigger 15, the transport guide 16, the roller 17, and the like are displayed on the graphic screen 13 in the display device 12. FIG. 4 shows a state in which the periphery of the sensor trigger 15 is enlarged and displayed. As shown in FIG. 4, a plurality of segments consisting of a line and two end points at both ends thereof are displayed. Further, segment numbers L1, L2,... L13 are displayed for each segment, and end point numbers n1, n2,... N24 are displayed for each end point. As shown in FIGS. 3 and 4, a part of the segment of the sensor trigger 15 and a part of the segment of the conveyance guide 16 are overlapped.

  When the closed loop automatic recognition apparatus shown in FIG. 1 reads the CAD data as described above, the information of each segment number and each end point number is stored in the hard disk 8 from the acquired CAD data in step S1. The data structure of this information is shown in FIG. Furthermore, information on each end point number and the coordinates of the end point is stored in the hard disk 8 from the acquired CAD data. The data structure of this information is shown in FIG.

  Next, in step S2, the user is requested to designate one of the segments. Here, it is assumed that the segment L1 is designated via a mouse pointer which is one of the input devices 10. If such designation is made, a member number of the member to which the designated segment L1 belongs is newly defined in step S4 after step S3. Here, it is assumed that the member number “1” is defined.

  Next, in step S5, information on the member number “1” defined in step S4 and the segment number L1 of the segment specified by the user is stored in the hard disk 8. The data structure of this information is shown in FIG. As shown in FIG. 7, the member number “1” and the segment number “L1” of the segment belonging to the member are stored.

Thereafter, in step S6, the user is requested to set an allowable value. Here, it is assumed that “0.1” is input as the allowable value T in the command column 14. If there is such a setting, after step S7, in step S8, an end point in the vicinity of one end point n2 of the two end points constituting the segment L1 designated by the user is extracted. Here, the reason why the end point n2 is selected instead of the end point n1 is that the process is simply proceeded clockwise, and the end point n1 may be selected as proceeding counterclockwise. In the extraction process in step S8, first, the coordinates of the end point n2 are read from the information shown in FIG. That is, the coordinates (X, Y) = (3.1000, -1.5000) of the end point n2 are read. Then, from the set allowable value T = 0.1 mm, as shown in FIG. 8, endpoints satisfying the following conditions, that is, endpoints located in a predetermined square area are extracted.
3.1000-0.1 <X coordinate of end point <3.1000 + 0.1
−1.5000−0.1 <Y coordinate of the end point <−1.5000 + 0.1

  As a result, an end point n3 whose coordinates are (3.1001, -1.4998) is extracted. In step S8, this process is further counted as an extraction step, and the number of this extraction step, the end point serving as the extraction reference, and information on the extracted end point are stored in the hard disk 8. The data structure of this information is shown in FIG.

  Next, in step S9, the segment number of segment L2 is additionally recorded in the information created in step S5. The result is shown in FIG.

  In step S10, it is determined whether the segment L2 that is a segment including the end point n3 is a segment designated by the user. Here, since the segment L2 is not a segment designated by the user, the process proceeds to step S11.

Subsequently, in step S11, an end point in the vicinity of the other end point n4 of the segment L2 is extracted. In this extraction process, as in step S8, first, the coordinates of the end point n4 are read from the information shown in FIG. That is, the coordinates (X, Y) = (4.8500, 6.5000) of the end point n4 are read. Then, from the set allowable value T = 0.1 mm, endpoints satisfying the following conditions, that is, endpoints located in a predetermined square area are extracted.
4.8500-0.1 <X coordinate of end point <4.8500 + 0.1
6.5000-0.1 <Y coordinate of the end point <6.5000 + 0.1

  As a result, as shown in FIG. 11, an end point n5 whose coordinates are (4.8502, 6.5030) is extracted. In step S11, this process is further counted as an extraction step, and the number of the extraction step, the end point serving as the extraction reference, and the information on the extracted end point are additionally recorded in the hard disk 8. The result is shown in FIG.

  And it returns to step S9 and repeats the process of step S9-S11 until it determines with it being the segment L1 in step S10. That is, in the example shown in FIG. 4, in the subsequent step S9, the segments L3, L4, L5, L6, and L1 are additionally recorded on the hard disk 8 in this order. The result is shown in FIG. In step S10 immediately after that, it is determined that the segment L1 is designated by the user. Therefore, in step S12, the segment recorded as the segment constituting the member number 1 is highlighted in the information shown in FIG. As a highlighting method, for example, the color of the line is changed and the thickness is increased as shown in FIG.

  Then, after step S12, the closed loop automatic recognition processing is terminated.

  According to the first embodiment, a segment constituting a closed loop is searched for while repeating the process of extracting an end point that satisfies a certain condition from the coordinate information of the end point. Therefore, even when there are a plurality of members in the read CAD data or the created CAD data and a very large number of segments are the targets of the closed loop automatic recognition processing, it is possible to reliably and easily acquire a desired closed loop. Can do. That is, a closed loop is surely recognized regardless of whether the segments intersect or not. Moreover, since the range to be extracted is limited, the calculation time required for extraction can be shortened.

  Further, since the closed loop is highlighted, the user can easily recognize the shape of the member.

(Second Embodiment)
Next, a second embodiment of the present invention will be described. In the first embodiment, when extracting the end points, the end points located in the square area are searched. In the second embodiment, the distances between the reference end point and all other end points are calculated. , Search for a distance that is less than the allowable value.

  For example, when searching for an end point based on the end point n2, as shown in FIG. 15, the distance between the end point n2 and all other end points is calculated, and the distance is set to a set allowable value T = 0. Extract everything that is 1 mm or less. Also by this processing, only the end point n3 is extracted as in the first embodiment. In FIG. 15, some end points are omitted in order to prevent the drawing from becoming too fine, but the result does not change.

  Other processes are the same as those in the first embodiment.

  According to the second embodiment as described above, the same effect as that of the first embodiment can be obtained. However, in the second embodiment, since the distance between one end point and all other end points is calculated, the number of segments subject to closed loop automatic recognition processing is small and the end points are concentrated. It is particularly effective. It is also particularly effective when the distance between the end points of the segments constituting the closed loop is known in advance.

(Third embodiment)
Next, a third embodiment of the present invention will be described. In the CAD data shown in FIG. 4, there is always one endpoint extracted when searching for endpoints. However, in the CAD data shown in FIG. 16, there are a plurality of endpoints located near the endpoint n4. In the first and second embodiments, the result desired by the user may not be obtained. The third embodiment can avoid such a problem. FIG. 17A is a flowchart showing a part of processing of the closed-loop automatic recognition method according to the third embodiment of the present invention, and FIG. 17B shows another part of processing of the closed-loop automatic recognition method according to the third embodiment. It is a flowchart to show.

  In the present embodiment, first, similarly to the first embodiment, the processing up to step S9 is performed. Next, as shown in FIG. 17A, it is determined whether there are a plurality of end points extracted in step S8. If the extracted end point is singular, the process proceeds to step S10 as it is. On the other hand, if there are a plurality of extracted end points, one end point that has not yet been selected is selected from the plurality of extracted end points in step S32. Thereafter, the determination in step S10 is performed.

  Further, when the segment including the extracted end point is not designated by the user, as shown in FIG. 17B, it is determined whether the number of extraction steps has reached the specified number after step S10. Here, it is preferable that the specified number of times is generally larger than the number of segments (several tens to several hundreds at most) constituting one part, for example, 1000 times. The specified number of times may be set before the automatic recognition process, or may be set after the process is started until the process proceeds to step S33. If the specified number has not been reached, the process proceeds to step S11. Thereafter, the process returns to step S9 as in the first embodiment, and further, as shown in FIG. 17A, it is determined whether there are a plurality of extracted end points in step S31.

  On the other hand, if the number of extraction steps has reached the specified number, it is determined that the end point selected in the most recent step S32 is incorrect, and in step S34, the information on the end point selected in the most recent step S32 is deleted.

  Next, in step S35, information such as the segment number stored in the processing after the most recent step S32 is deleted.

  Next, in step S36, the process jumps to the nearest step S32, and an end point not yet selected is selected. At this time, if there is no unselected end point, it is sufficient to jump to the next nearest step S32.

  Then, as in the first embodiment, the processes in steps S9 to S11 including steps S31 to S36 are repeated until the segment designated by the user is extracted in step S10.

  For example, in the CAD data example shown in FIG. 16, when the segment L1 is designated by the user as in the first embodiment, in step S8, only the end point n2 is extracted, and in step S11 immediately after that. , End point n4 is extracted. Further, in the next step S11, end points n5, n25 and n26 are extracted. As a result, the information shown in FIG. 18 is additionally recorded on the hard disk 8.

  Next, in step S9, the information shown in FIG. In subsequent step S31, it is determined that a plurality of end points have been extracted, and in step S32, one of the three end points is selected. At this time, if the end point n5 is selected, the subsequent processing is substantially the same as that of the first embodiment. However, for example, if the end point n25 is selected, it is greatly different from the first embodiment.

  That is, when the end point n25 is selected, in step S11 immediately thereafter, the end point n23 is extracted with reference to the other end point n24 of the segment L13 including the end point n25, and in step S11 immediately thereafter, the end point n21 is extracted. . As a result, the information shown in FIG. 20 is additionally recorded on the hard disk 8. In step S9 immediately after that, the information shown in FIG.

  Thereafter, the processes of steps S9 to S11 including steps S31 to S33 are repeatedly performed. However, depending on the segment configuration of the conveyance guide 16, the extraction may not be returned to the segment L1 even if the extraction step is performed 1000 times. In this case, after step S33, in step S34, the information of the end point selected in the latest step S32, that is, the information of the end point n25 is deleted from the information shown in FIG.

  Subsequently, in step S35, information such as the segment number stored in the processing after the most recent step S32 is deleted. For example, segment numbers “L13”, “L12”, “L11” in FIG. 21 and extraction step numbers “3”, “4”, extraction reference end points “n24”, “n22”, extraction end points in FIG. “N23” and “n21” are deleted.

  In step S36, the process jumps to the nearest step S32 and selects an end point not yet selected, that is, an end point n5 or n26. When the end point n26 is selected, as in the case where the end point n25 is selected, the end point n5 is selected because it does not return to the segment L1 by the specified number of times. When the end point n5 is selected, as described above, since the process similar to that in the first embodiment is performed thereafter, a desired closed loop is obtained.

  Thus, according to the third embodiment, a desired closed loop can be obtained even when a plurality of end points are extracted at a time.

(Fourth embodiment)
Next, a fourth embodiment of the present invention will be described. According to the third embodiment, it is possible to select an appropriate end point when selection of an end point is incorrect and a continuum of segments in the vicinity of the end points does not return to the desired closed loop. It is. However, in the CAD data shown in FIG. 22, if there is an end point error, the continuum of segments may return to the desired closed loop, and an inappropriate closed loop may be formed as it is. The fourth embodiment can avoid such a problem. FIG. 23 is a flowchart showing a part of the process of the closed-loop automatic recognition method according to the fourth embodiment of the present invention. Note that the processing shown in FIG. 17A is also performed in the fourth embodiment.

  In the present embodiment, first, similarly to the third embodiment, the processing up to step S10 is performed. If the segment including the extracted end point is not the segment designated by the user, as shown in FIG. 22, it is determined whether or not the segment number is stored in duplicate in step S41. And if it cannot be stored redundantly, it will transfer to step S11 as it is. Thereafter, the process returns to step S9 as in the third embodiment.

  On the other hand, if the segment number is stored in duplicate, the end point selected in the most recent step S32 is determined to be an error, and in step S42, the information on the end point selected in the most recent step S32 is deleted.

  Next, in step S43, information such as the segment number stored in the processing after the most recent step S32 is deleted.

  Next, in step S44, the process jumps to the latest step S32, and an end point not yet selected is selected. At this time, if there is no unselected end point, it is sufficient to jump to the next nearest step S32.

  Then, similarly to the first embodiment, the processes in steps S9 to S11 including steps S31 to S32 and steps S41 to S44 are repeated until the segment designated by the user is extracted in step S10.

  For example, in the CAD data example shown in FIG. 22, when the segment L1 is designated by the user as in the first embodiment, only the end point n2 is extracted in step S8, and in step S11 immediately thereafter. , End point n4 is extracted. Further, in the next step S11, the end points n5, n25, and n26 are extracted as in the third embodiment. As a result, the information shown in FIG. 18 is additionally recorded on the hard disk 8.

  Next, in step S9, the information shown in FIG. In subsequent step S31, it is determined that a plurality of end points have been extracted, and in step S32, one of the three end points is selected. At this time, if the end point n5 is selected, the subsequent processing is substantially the same as that of the first embodiment. However, for example, if the end point n25 is selected, it is greatly different from the first embodiment.

  That is, when the end point n25 is selected, in step S11 immediately thereafter, the end point n23 is extracted with reference to the other end point n24 of the segment L13 including the end point n25, and in step S11 immediately thereafter, the end point n21 is extracted. . As a result, the information shown in FIG. 20 is additionally recorded on the hard disk 8 as in the third embodiment. In step S9 immediately after that, the information shown in FIG.

  Thereafter, when the processing is further advanced, information shown in FIGS. 24 and 25 is created. That is, information including the segment number “L14” is created. In this case, after step S41, in step S42, the information of the end point selected in the latest step S32, that is, the information of the end point n25 is deleted from the information shown in FIG.

  Subsequently, in step S43, the information such as the segment number stored in the processing after the latest step S32 is deleted. For example, segment numbers “L13”, “L12”, “L11”, “L15”, “L14” in FIG. 25 and extraction step numbers “3” to “6” in FIG. “N24” to “n28” and extracted end points “n23” to “n27” are deleted.

  In step S44, the process jumps to the nearest step S32 and selects an end point not yet selected, that is, an end point n5 or n26. When the end point n26 is selected, only the process in the reverse direction to that when the end point n25 is selected is performed, so the segment number “L13” is stored redundantly, and the end point n5 is eventually selected. . When the end point n5 is selected, as described above, since the process similar to that in the first embodiment is performed thereafter, a desired closed loop is obtained.

  As described above, according to the fourth embodiment, a desired closed loop can be obtained even when a plurality of end points are extracted at a time.

(Fifth embodiment)
Next, a fifth embodiment of the present invention will be described. Even with the first to fourth embodiments, as shown in FIG. 26, if a confusing line is included in the CAD data, the result intended by the user may not be obtained. In the fifth embodiment, the user can make corrections in such a case. FIG. 27 is a flowchart showing a part of processing of the closed-loop automatic recognition method according to the fifth embodiment of the present invention.

  In the present embodiment, the processes in steps S1 to S12 are performed as in the fourth embodiment. Then, as shown in FIG. 27, in step S51, the user is confirmed whether the highlighted closed loop is intended.

  In step S52, if there is a response indicating that the user is in a desired closed loop, the processing is terminated as it is. On the other hand, if there is a response indicating that it is not the desired closed loop, the process proceeds to step S53, and the user is requested to specify which segment is initially out of the desired closed loop.

  Next, in step S54, it is determined whether or not there is a designation from the user. When a segment that has been removed first is designated, the information on the endpoint included in the segment is deleted.

  Next, in step S56, information such as the segment number stored in the processing after step S32 in which the end point is selected is deleted.

  Thereafter, in step S57, the process jumps to step S32 in which the end point is selected, and an end point not yet selected is selected. At this time, if there is no unselected end point, it is sufficient to jump to the next nearest step S32.

  In step S52, the processes in steps S9 to S11 including steps S51 to S57 are repeated until there is a response indicating that the intended closed loop has been obtained.

  For example, in the highlighting shown in FIG. 26, the information shown in FIGS. 28 and 29 is stored in the hard disk 8. Since highlighting is performed in this state, the user designates the segment L13 in response to the request in step S53. When this designation is made, in step S55, the extracted end point information of the segment L13, that is, the end point n25 information is deleted from the information shown in FIG.

  Subsequently, in step S56, information such as the segment number stored in the processing after step S32 in which the end point n25 is selected is deleted. For example, segment numbers “L13”, “L12”, “L11”, “L15”, “L101”, “L5”, “L6”, “L1” in FIG. 29 and extraction step number “3” in FIG. Thereafter, the extraction reference end point information and the extracted end point information corresponding to these are deleted.

  In step S57, the process jumps to step S32 in which the end point n25 is selected, and the end point not yet selected, that is, the end point n5 or n26 is selected. If the end point n26 is selected, the end point n5 is eventually selected by the same processing as in the fourth embodiment, or even if a closed loop is created, it is not desired in step S52. In response, end point n5 will be selected. When the end point n5 is selected, as described above, since the process similar to that in the first embodiment is performed thereafter, a desired closed loop is obtained. Then, in step S52, there is a response indicating that it is desired, and the process ends.

  According to the fourth embodiment, even if the user's intention is not reflected at first, the closed loop can be easily corrected thereafter.

  Note that the first or second embodiment and the third to fifth embodiments may be used in appropriate combination. In this case, a synergistic effect more than the sum of the effects of the embodiments can be obtained.

  The embodiment of the present invention can be realized by, for example, a computer executing a program. Also, means for supplying a program to a computer, for example, a computer-readable recording medium such as a CD-ROM recording such a program, or a transmission medium such as the Internet for transmitting such a program is also applied as an embodiment of the present invention. Can do. The above program can also be applied as an embodiment of the present invention. The above program, recording medium, transmission medium, and program product are included in the scope of the present invention.

It is a block diagram which shows the structure of the closed loop automatic recognition apparatus which concerns on the 1st Embodiment of this invention. It is a flowchart which shows the closed loop automatic recognition method in 1st Embodiment. It is a figure which shows an example of CAD data containing the data of the sensor trigger of a paper conveyance assistance system. It is a figure which shows the state which expanded and displayed the periphery of the sensor trigger. It is a figure which shows the data structure of the information stored in step S1. It is a figure which shows the data structure of the other information stored in step S1. It is a figure which shows the data structure of the information stored in step S4. It is a figure which shows the extraction step of an end point. It is a figure which shows the data structure of the information stored in step S8. It is a figure which shows the data structure of the information in which the additional recording in step S9 was performed. It is a figure which shows the extraction step of another end point. It is a figure which shows the data structure of the information in which the additional recording in step S11 was performed. It is a figure which shows the data structure of the information in which the additional recording in subsequent step S9 was performed. It is a figure which shows the closed loop highlighted. It is a figure which shows the closed loop automatic recognition method which concerns on the 2nd Embodiment of this invention. It is a figure which shows another example of CAD data containing the data of the sensor trigger of a paper conveyance assistance system. It is a flowchart which shows a part of process of the closed loop automatic recognition method in the 3rd Embodiment of this invention. It is a flowchart which shows a part of other processes of the closed loop automatic recognition method in 3rd Embodiment. It is a process with respect to the example shown in FIG. 16, and is a figure which shows the data structure of the information in which the additional recording in step S11 was performed. It is a process with respect to the example shown in FIG. 16, and is a figure which shows the data structure of the information in which the additional recording in step S9 was performed. FIG. 17 is a diagram illustrating a data configuration of information that is additionally recorded in a subsequent step S11 in the process for the example illustrated in FIG. 16; FIG. 17 is a diagram illustrating a data configuration of information on which additional recording is performed in the subsequent step S9 in the process for the example illustrated in FIG. It is a figure which shows another example of CAD data containing the data of the sensor trigger of a paper conveyance assistance system. It is a flowchart which shows a part of process of the closed-loop automatic recognition method in the 4th Embodiment of this invention. FIG. 23 is a diagram illustrating a data configuration of information on which additional recording is performed in step S11 in the process for the example illustrated in FIG. 22; FIG. 23 is a diagram illustrating a data configuration of information that has been additionally recorded in step S9 in the process for the example illustrated in FIG. 22; It is a figure which shows the closed loop which the user does not intend. It is a flowchart which shows a part of process of the closed-loop automatic recognition method in the 5th Embodiment of this invention. FIG. 27 is a diagram illustrating a data configuration of information that has been additionally recorded in step S11 in the process for the example illustrated in FIG. FIG. 27 is a diagram illustrating a data configuration of information that has been additionally recorded in step S9 in the process for the example illustrated in FIG. 26.

Explanation of symbols

8: Hard disk 9: Memory 10: Input device 11: CPU
12: Display device

Claims (9)

A closed loop automatic recognition device for recognizing a closed loop configured by combining a plurality of segments each represented by a line,
Input means for inputting a user designation for one of the plurality of segments;
A tolerance value input means for inputting a tolerance value relating to the distance between the end points of the adjacent segments that can be permitted in the recognition of the closed loop;
First extraction means for extracting from the one end point of the designated segment the other end point within the tolerance range;
Second extraction means for extracting an end point of another segment within the allowable value range from the other end point of the segment including the end point extracted by the first end point extraction means;
When the segment including the end point extracted by the second extraction unit matches the segment designated via the input unit, the group consisting of a plurality of segments including the end point extracted so far is specified as a closed loop. Means,
Highlighting means for highlighting the closed loop identified by the identifying means;
Have
The second extracting means includes the end point extracted by the first extracting means until the segment including the extracted end point matches the segment designated via the input means. deemed to, to repeat the extraction end point of the other segments,
When there are two or more segments including an end point that falls within the allowable range, the first extracting unit continues the extraction after arbitrarily selecting one segment from the two or more segments, If the selection by the second extraction means does not coincide with the segment designated via the input means even if the extraction is performed a predetermined number of times, it is determined that the selection is erroneous and the two or more A closed loop automatic recognition apparatus characterized by selecting another one of the segments and then continuing the extraction by the second extraction means again .   The closed loop automatic recognition apparatus according to claim 1, further comprising storage means for storing the plurality of segments, the configuration information of the end points of the segments, and the coordinates of the end points.   When the first and second extraction means represent the coordinates of the end point as (X, Y) and represent the allowable value as T, “X−T <X coordinate of the end point <X + T” and “Y− The closed loop automatic recognition apparatus according to claim 1, wherein other end points satisfying a relationship of T <Y coordinate of end points <Y + T ”are extracted.   2. The closed loop automatic recognition device according to claim 1, wherein the first and second extraction units extract other end points whose distance from the end point is equal to or less than a distance represented by the allowable value. When there are two or more segments including an end point that falls within the allowable range, the first extracting unit continues the extraction after arbitrarily selecting one segment from the two or more segments, When an end point included in a segment different from the segment specified via the input means is detected twice, another one of the two or more segments is selected as the selection is incorrect. Then, the closed loop automatic recognition apparatus according to any one of claims 1 to 4 , wherein the extraction by the second extraction unit is continued again. When there are two or more segments including an end point that falls within the allowable range, the first extracting unit continues the extraction after arbitrarily selecting one segment from the two or more segments, Even though one closed loop is specified by the specifying means, when the closed loop is erroneous and an end point included in a segment that first deviates from the closed loop to be recognized is extracted by the second extracting means. , after selecting another first segment of the two or more segments, according to any one of claims 1 to 5, characterized in that re-continue the extraction with the second extraction means Closed loop automatic recognition device. A closed loop automatic recognition method for recognizing a closed loop configured by combining a plurality of segments each represented by a line,
An input step of inputting a user designation for one of the plurality of segments;
A tolerance value input step of inputting a tolerance value regarding the distance between the end points of the adjacent segments that can be permitted in the recognition of the closed loop;
A first extraction step of extracting, from one end point of the designated segment, another end point within the tolerance range;
A second extraction step of extracting an end point of another segment within the allowable range from the other end point of the segment including the end point extracted in the first end point extraction step;
When the segment including the end point extracted in the second extraction step matches the segment specified in the input step, a specifying step of specifying a group of a plurality of segments including the end point extracted so far as a closed loop;
A highlighting step of highlighting the closed loop identified in the identifying step;
Have
In the second extraction step, the endpoint extracted in the second extraction step is extracted in the first extraction step until the segment including the extracted endpoint matches the segment specified in the input step. is regarded as the end point, have a step of repeating the extraction of the end point of another segment,
In the first extraction step, when there are two or more segments including end points that fall within the allowable value range, the extraction is continued after arbitrarily selecting one segment from the two or more segments, Even if the extraction of the second extraction step is performed a predetermined number of times that is determined in advance, when the selected segment does not match the segment specified via the input means, in it selects another first segment of the segments, a closed loop automatic recognition method characterized by it has a step of re-continue the extraction of the second extraction step. A program for causing a computer to execute each means of the closed-loop automatic recognition device according to any one of claims 1 to 6 . A computer-readable recording medium on which the program according to claim 8 is recorded.

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