JP3013301B2 - Degradation evaluation method of steel surface using image processing - Google Patents
Degradation evaluation method of steel surface using image processingInfo
- Publication number
- JP3013301B2 JP3013301B2 JP9228800A JP22880097A JP3013301B2 JP 3013301 B2 JP3013301 B2 JP 3013301B2 JP 9228800 A JP9228800 A JP 9228800A JP 22880097 A JP22880097 A JP 22880097A JP 3013301 B2 JP3013301 B2 JP 3013301B2
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- steel material
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- 229910000831 Steel Inorganic materials 0.000 title claims description 34
- 239000010959 steel Substances 0.000 title claims description 34
- 238000011156 evaluation Methods 0.000 title claims description 21
- 238000012545 processing Methods 0.000 title claims description 12
- 230000015556 catabolic process Effects 0.000 title claims description 8
- 238000006731 degradation reaction Methods 0.000 title claims description 8
- 239000000463 material Substances 0.000 claims description 39
- 230000006866 deterioration Effects 0.000 claims description 35
- 229910001335 Galvanized steel Inorganic materials 0.000 claims description 11
- 230000007797 corrosion Effects 0.000 claims description 11
- 238000005260 corrosion Methods 0.000 claims description 11
- 239000008397 galvanized steel Substances 0.000 claims description 11
- 238000000034 method Methods 0.000 claims description 11
- 239000003086 colorant Substances 0.000 claims description 10
- 239000013598 vector Substances 0.000 claims description 7
- JEIPFZHSYJVQDO-UHFFFAOYSA-N iron(III) oxide Inorganic materials O=[Fe]O[Fe]=O JEIPFZHSYJVQDO-UHFFFAOYSA-N 0.000 claims description 6
- 238000005246 galvanizing Methods 0.000 claims description 3
- 239000000654 additive Substances 0.000 claims description 2
- 230000000996 additive effect Effects 0.000 claims description 2
- 238000003384 imaging method Methods 0.000 claims 1
- 238000011835 investigation Methods 0.000 claims 1
- 239000000203 mixture Substances 0.000 claims 1
- XEEYBQQBJWHFJM-UHFFFAOYSA-N Iron Chemical compound [Fe] XEEYBQQBJWHFJM-UHFFFAOYSA-N 0.000 description 6
- 238000010586 diagram Methods 0.000 description 6
- 229910045601 alloy Inorganic materials 0.000 description 5
- 239000000956 alloy Substances 0.000 description 5
- 229910052742 iron Inorganic materials 0.000 description 3
- 238000012360 testing method Methods 0.000 description 3
- HCHKCACWOHOZIP-UHFFFAOYSA-N Zinc Chemical compound [Zn] HCHKCACWOHOZIP-UHFFFAOYSA-N 0.000 description 2
- 238000006243 chemical reaction Methods 0.000 description 2
- 150000003839 salts Chemical class 0.000 description 2
- 239000007921 spray Substances 0.000 description 2
- 229910052725 zinc Inorganic materials 0.000 description 2
- 239000011701 zinc Substances 0.000 description 2
- 230000007547 defect Effects 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 239000001963 growth medium Substances 0.000 description 1
- 238000005259 measurement Methods 0.000 description 1
- 239000002609 medium Substances 0.000 description 1
- 238000010606 normalization Methods 0.000 description 1
- 230000002250 progressing effect Effects 0.000 description 1
- 238000011002 quantification Methods 0.000 description 1
- 238000005070 sampling Methods 0.000 description 1
- 229910052709 silver Inorganic materials 0.000 description 1
- 239000004332 silver Substances 0.000 description 1
Landscapes
- Investigating Or Analysing Materials By Optical Means (AREA)
- Spectrometry And Color Measurement (AREA)
- Investigating Materials By The Use Of Optical Means Adapted For Particular Applications (AREA)
Description
【発明の詳細な説明】
【０００１】
【産業上の利用分野】 本発明は、鋼材の腐食状態や、
溶融亜鉛メッキを施した鋼材の表面劣化状態を撮影した
写真から、撮影時に写し込んだグレイカードの色を補
正，現像することで色合いを統一し、スキャナなどを用
いて計算機に取り込み、色のＲ，Ｇ，Ｂ信号に基づく画
像処理を用いて明るさを補正することで、腐食状態・劣
化状態を定量的に評価する方法に関する。
【０００２】
【従来の技術】従来、構造物の鋼材の腐食状態や、溶融
亜鉛メッキを施した鋼材の表面劣化状態を評価するに
は、人の視覚や写真による評価に始まり、色標による評
価や、超音波によって鋼材の厚さを計測するものなどが
ある。しかし、人の視覚に頼る調査では、同じものを評
価しても定量的に判断するのは難しく、個人によってそ
の評価が異る問題が生じる。超音波測定においては、部
分部分は比較的定量的に評価が可能であるが、こと広い
範囲になると、評価に時間と労力がかかり、構造によっ
ては、測定できない個所も生じてくる問題があった。
【０００３】また、鋼材の腐食状態の写真を用いた、マ
ンセル表色系に基づく、Ｒ（赤），Ｇ（緑），Ｂ（青）
の３原色信号（以下Ｒ，Ｇ，Ｂ信号と略す）により、カ
ラー画像処理を行ない、個人差による評価の違いを防ぐ
方法を実施しても、異なる光源下で撮影されることによ
り鋼材の腐食状態は評価に違いを生じ、撮影条件の統一
化が必要であった。
【０００４】
【発明が解決しようとする課題】そこで、鋼材の腐食状
態の写真を用いて、撮影時に同写真内に写し込んだグレ
イカードの色を、マンセル表色計の加法混色の３原則の
なかで一般的なＲ（赤色），Ｇ（緑色），Ｂ（青色）を
使用し、Ｒ＝Ｇ＝Ｂとなるように補正，現像して、スキ
ャナなどを用いて画像を計算機にディジタル映像信号と
して取り込み、色のＲ，Ｇ，Ｂ信号に基づく画像処理の
基準化を行った上で評価してやることにより、異なった
光源条件下で、撮影された腐食状態および劣化状態を定
量化し、個人差による評価の違いを防ぐことを目的とし
た評価方法を、提案しようとするものである。
【０００５】
【課題を解決するための手段】上記目的を達成するため
に、本考案における評価方法は、まず鋼材の腐食状態を
写真に撮影する場合に、グレイカードが同写真内に入り
込むように撮影し、その現像時に、グレイカードのＲ，
Ｇ，Ｂ信号に基づく画像処理結果が、Ｒ＝Ｇ＝Ｂになる
ように補正しながら現像する。
【０００６】このようにして現像された写真（アナログ
映像）（
【図２】Ａ点）を、スキャナなどを用いてディジタル映
像の信号として計算機に取り込むために、ｘ方向（横方
向）（
【図２】Ｃ点）およびｙ方向（縦方向）（
【図２】Ｄ点）に細かく分解して、それぞれ四角で囲ま
れた画素（
【図２】Ｂ点）を設定する。各画素は、空間サンプリン
グされた後、Ａ／Ｄ変換によってディジタル映像信号に
変換されるが、このとき画素をできるだけ小さくとるこ
とで、アナログ映像とデイジタル映像信号との誤差が、
小さくなる。
【０００７】各画素の画像の明るさ（濃淡値）である階
調値は、マンセル表色系に基づく、Ｒ（赤），Ｇ
（緑），Ｂ（青）の３原色信号を用いた２ｎ（ｎは任意
数）段階で表され、表現可能な色数は、（２ｎ）３色で
ある。
【０００８】溶融亜鉛メッキを施された鋼材の、表面状
態の撮影された写真から劣化度を評価する基準値は、例
えば塩水噴霧試験などで定量的に表した表面状態から、
劣化度の段階を予め設定することで、
【数１】で明るさの統一化をされたＲＧＢ信号を用い
て、鋼材の劣化度の評価基準値が定義できる。もちろ
ん、劣化度の評価の区別は、状況や判断基準により、任
意に設定できる。
【０００９】鋼材の劣化度の段階ごとに、Ｒ，Ｇ，Ｂを
軸とする３次元直角座標系にプロットすると、
【図３】のように、全て半径（２ｎ−１）の球上の、決
まった位置にプロットされる。鋼材の任意位置での劣化
状態を、Ｒ’，Ｇ’，Ｂ’により表したベクトルの合力
を用いて、
【図４】の様に同グラフ中にプロットして、劣化度のプ
ロットと比較することにより、劣化状態の分布や広がり
の評価・確認を行うものである。
【００１０】また、溶融亜鉛メッキを施した鋼材表面に
おけるＲ，Ｇ，Ｂ信号の画像処理結果をプロットしたグ
ラフから、色合いに影響の強いＲＧ成分に注目するため
に、
【数２】に示す平面上に、プロット結果を投影し、ＲＧ
座標のＲ値により、腐食部分（錆）と、溶融亜鉛メッキ
層とを区別するものである。
【００１１】そして、鋼材表面におけるＲ’，Ｇ’，
Ｂ’をプロットしたグラフから、
【数２】に示す平面上に投影されたＲＧ成分を用いて、
劣化度の評価を行うものである。
【作用】
【００１２】上記のような作業により、溶融亜鉛メッキ
を施した鋼材表面における劣化状態をＲ，Ｇ，Ｂ信号の
画像処理結果によって統一化することで、撮影条件に依
存されない状態で予め定義してある劣化度と簡単に比較
でき、個人差による評価の違いを防げる。
【００１３】そして、鋼材の全表面範囲に広がる劣化状
態は、各画素における画像処理結果から
【数１】で求めたＲ’，Ｇ’，Ｂ’を、Ｒ，Ｇ，Ｂを軸
とする３次元直角座標系にプロットさせた集合により、
評価・定量化できる。
【００１４】また、Ｒ，Ｇ，Ｂを軸とする３次元直角座
標系にプロットさせたグラフを、
【数２】に示す平面上に投影したＲＢ成分から、初めに
定義したＲ値を判定値として、鋼材表面における、腐食
部分（錆）と、溶融亜鉛メッキ層とを、簡単に区別する
ことができる。
【００１５】さらに、ＲＧ成分からは、鋼材表面におけ
る溶融亜鉛メッキ層の劣化状態も評価・定量化できる。
【実施例】
【００１６】以下、本発明の実施例を詳細に説明する。
【図２】は、鋼材表面の画像の明るさを評価するため、
鋼材の表面状態を撮影した写真（
【図２】Ａ点）を格子で仕切った図である。格子は、画
素（
【図２】Ｂ点）とも呼ばれ、画像の大きさや解像度を表
す。各画素の位置における画像の明るさ（濃淡値）を、
階調若しくは階調値と呼ぶ。階調画像では、階調数が大
きくなるほど画質が高い。本発明では、カラー画像にマ
ンセル表色系のＲ（赤），Ｇ（緑），Ｂ（青）の３原色
信号を用いて、各画素を表してやり、画素の階調をＲ，
Ｇ，Ｂ各８ビット、すなわち２８＝２５６段階とすると
き、鋼材の表面状態について表現可能な色数は、２５６
３＝１６７７７２１６≒１６８０万色になる。
【００１７】写真は、撮影状況の違いにより色の明るさ
の違いが生じるため、鋼管内を内視鏡で撮影した写真
と、太陽の下で撮影した写真とでは、評価結果が異なる
と考えられる。そこで、各写真に写し込んだグレイカー
ドの色を、現像の時点で調整することで、色合いの統一
化を行い、各画素のアナログ映像信号を空間サンプリン
グした後、Ａ／Ｄ変換を行って、ディジタル映像信号と
して計算機に取り込む。
【００１８】この際、サンプリングの幅をできるだけ小
さくすることで、ディジタル映像信号とアナログ映像信
号との誤差が小さくなるため、鋼材の劣化度を、ディジ
タル映像信号として色のＲ，Ｇ，Ｂ信号で表し、
【数１】に従い、（Ｒ’，Ｇ’，Ｂ’）に基準化を行
う。
【数１】において、ｎ＝８とすると、統一化された
Ｒ’，Ｇ’，Ｂ’は、２５５段階で表現できる。
【００１９】溶融亜鉛メッキを施した鋼材の劣化度は、
予め塩水噴霧試験のような試験結果より、
【図５】に示す溶融亜鉛メッキ皮膜の組織図の、Ｉ）η
層（亜鉛層）（
【図５】Ｅ点）が残っている状態で、銀色あるいは灰色
を呈する，ＩＩ）η層が減耗し、ζ層（上合金層）（
【図５】Ｆ点）が露出した状態で、褐色若しくは黒褐色
を呈する，ＩＩＩ）ζ層が減耗しδ１層（中合金層）（
【図５】Ｇ点）が露出した状態で、赤褐色若しくは斑点
状に赤褐色を呈する，ＩＶ）δ１層が減耗し、Γ層（下
合金層）（
【図５】Ｈ点）が露出した状態で、赤褐色若しくは斑点
状に赤褐色を呈する，Ｖ）Γ層が減耗し、鋼材が露出し
た状態で赤褐色を呈する，と定量的に表すことで、評価
基準値を設定してやる。評価基準値を、Ｒ，Ｇ，Ｂを軸
とする３次元直角座標系にプロットすると、Ｒ’，
Ｇ’，Ｂ’は、２５５段階で表現される場合、
【図３】のように、全て半径２５５の球上の、決まった
位置にプロットされる。
【００２０】劣化状態の色の明るさを統一化したＲ’，
Ｇ’，Ｂ’で表し、Ｒ，Ｇ，Ｂを３軸とする直交座標
に、画像中の画素すべてをプッロトして、
【図４】で示すような評価基準値と比較することによ
り、劣化状態の分布や広がりを定量的に評価でき、個人
差による評価の違いを防げる。
【００２１】このとき、画素は小さいほど、精度よく表
面の状態を把握できる。そして、
【図４】で示すプロットにより、色が濃いところが、最
もその鋼材の表面状態を、表しているところである。
【００２２】また、溶融亜鉛メッキを施した鋼材に発生
する腐食（錆）は、溶融亜鉛メッキ皮膜組織のΓ層を超
えて、鉄地にまで断面欠損が進んだ結果であり、溶融亜
鉛メッキ部の劣化状態とは、明るさを統一化したＲ’，
Ｇ’，Ｂ’で、色合いが異なる。
【００２３】そのため、劣化状態をＲ’，Ｇ’，Ｂ’で
表し、Ｒ，Ｇ，Ｂを３軸とする直交座標に、画像中の画
素すべてをプッロトした結果を、
【数２】に示す平面上に投影し、ＲＧ成分だけに注目す
ると、
【図５】のように、鉄地の腐食により定義されたＲ値を
判定値として、ＲＧ座標により、鋼材表面における、腐
食部分（錆）と、溶融亜鉛メッキ層とを、簡単に区別す
ることができる。
【００２４】そして、このＲＧ座標は、予め定量的に表
されている評価基準値と比較することで、溶融亜鉛メッ
キを施した鋼材の劣化度を定量的に評価でき、個人差に
よる評価の違いを防げる。
【００２５】
【発明の効果】本発明は、以上に説明した手順で行うこ
とにより、以下に記載するような効果を奏する。
【００２６】
【請求項１】の方法について、溶融亜鉛メッキを施した
鋼材の劣化状況写真を、撮影時に写し込んだグレイカー
ドの色がＲ＝Ｇ＝Ｂとなるように色合いを補正，現像
し、スキャナなどを用いて計算機に取り込み、色のＲ，
Ｇ，Ｂ信号に基づく画像処理を施す場合に、様々な状況
下で撮影された写真の明るさ（ベクトル長さ）が統一さ
れた値となるため、撮影状況に依存しない劣化状態の評
価ができる。
【００２７】
【請求項２】の方法について、溶融亜鉛メッキを施した
鋼材の劣化状況写真を、
【請求項１】で示す方法に従って画像処理することによ
り、劣化状態の色の明るさを統一化した値Ｒ’，Ｇ’，
Ｂ’でベクトル表示された合力を用いて、画像中の全て
の点をプロットすることができ、予め設定しておいた評
価基準値と簡単に比較して、劣化状態の分布や広がりを
確認することができる。
【００２８】
【請求項３】の方法について、溶融亜鉛メッキを施した
鋼材の写真の評価が、撮影状況に依存しないように、
【請求項１】で示す方法に従い、任意位置での劣化状況
をＲ’，Ｇ’，Ｂ’で表し、Ｒ，Ｇ，Ｂを３軸とする直
交座標により色をベクトル表示し、
【数２】で示す平面に投影して、そのＲＧ成分のみ使用
することで、鋼材の腐食（錆）と溶融亜鉛メッキ層を区
別および、劣化度の評価ができる。Description: BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention
From the photograph of the surface degradation of the galvanized steel material, the color of the gray card captured at the time of photography is corrected and developed to unify the color, and the color is unified into a computer using a scanner or the like. The present invention relates to a method for quantitatively evaluating a corrosion state and a deterioration state by correcting brightness using image processing based on G, B signals. 2. Description of the Related Art Conventionally, to evaluate the corrosion state of a steel material of a structure or the surface deterioration state of a hot-dip galvanized steel material, it starts with an evaluation by a human eye or a photograph, and then by an evaluation of a color mark. And those that measure the thickness of a steel material by ultrasonic waves. However, in a survey that relies on human vision, it is difficult to make a quantitative determination even when evaluating the same thing, and there is a problem that the evaluation differs depending on the individual. In ultrasonic measurement, it is possible to relatively quantitatively evaluate the partial part, but if it is a very wide range, it takes time and effort to evaluate, and depending on the structure, there is a problem that some parts can not be measured . Further, R (red), G (green), B (blue) based on the Munsell color system using photographs of the corrosion state of steel materials.
However, even if color image processing is performed using the three primary color signals (hereinafter abbreviated as R, G, and B signals) to prevent a difference in evaluation due to individual differences, corrosion of steel due to photographing under different light sources will occur. The condition caused a difference in the evaluation, and it was necessary to standardize the shooting conditions. [0004] Therefore, using a photograph of the corrosion state of a steel material, the color of the gray card imprinted in the photograph at the time of photographing using the photograph of the corrosion state of the steel material is determined by the three principles of additive color mixing of the Munsell colorimeter. Among them, common R (red), G (green), and B (blue) are used, corrected and developed so that R = G = B, and an image is sent to a computer using a scanner or the like. By performing standardization of image processing based on the R, G, and B signals of colors and evaluating the results, quantification of the corroded and degraded states photographed under different light source conditions is performed. An attempt is made to propose an evaluation method aimed at preventing differences in evaluation. [0005] In order to achieve the above object, an evaluation method according to the present invention is designed such that when a corrosion state of steel material is photographed first, a gray card is inserted into the photograph. When shooting and developing it, R,
The image is developed while correcting the image processing result based on the G and B signals so that R = G = B. The photograph (analog video) (point A in FIG. 2) developed in this way is taken into a computer as a digital video signal by using a scanner or the like. (2) Point C) and y-direction (vertical direction) (FIG. 2, point D) are finely divided to set pixels (FIG. 2, point B) enclosed by squares, respectively. After each pixel is spatially sampled, it is converted into a digital video signal by A / D conversion. At this time, by taking the pixel as small as possible, an error between the analog video and the digital video signal is reduced.
Become smaller. [0007] The gradation value, which is the brightness (shade value) of the image of each pixel, is represented by R (red), G (G) based on the Munsell color system.
It is expressed in 2 n (n is an arbitrary number) stages using three primary color signals of (green) and B (blue), and the number of expressible colors is (2 n ) three colors. [0008] The reference value for evaluating the degree of deterioration from a photograph of the surface state of a steel material subjected to hot-dip galvanization is obtained from the surface state quantitatively represented by, for example, a salt spray test.
By setting the stage of the degree of deterioration in advance, the evaluation reference value of the degree of deterioration of the steel material can be defined using the RGB signals whose brightness is unified by the following equation. Of course, the evaluation of the degree of deterioration can be arbitrarily set according to the situation or the criterion. When plotted on a three-dimensional rectangular coordinate system with R, G, and B as axes for each stage of the degree of deterioration of the steel material, as shown in FIG. 3, all spheres of radius (2 n -1) are obtained. Is plotted in a fixed position. The degradation state of the steel material at an arbitrary position is plotted in the same graph as in FIG. 4 using the resultant force of the vectors represented by R ′, G ′, and B ′, and compared with the degradation degree plot. In this way, the distribution and spread of the deterioration state are evaluated and confirmed. From the graph plotting the image processing results of the R, G, B signals on the surface of the hot-dip galvanized steel material, in order to focus on the RG component that has a strong influence on the color tone, Above, project the plot result, RG
The corroded portion (rust) and the hot-dip galvanized layer are distinguished by the R value of the coordinates. [0011] Then, R ', G',
From the graph plotting B ′, using the RG component projected on the plane shown in
This is to evaluate the degree of deterioration. By the above operation, the deterioration state on the surface of the steel material subjected to the hot-dip galvanization is unified by the image processing results of the R, G, B signals, so that the deterioration state can be previously determined without depending on the photographing conditions. It can be easily compared with the defined deterioration degree, and the difference in evaluation due to individual differences can be prevented. The deterioration state spreading over the entire surface area of the steel material is calculated by using R ′, G ′, B ′ obtained from the image processing result of each pixel by the following equation (1), with R, G, and B as axes. By the set plotted in the three-dimensional rectangular coordinate system,
Can be evaluated and quantified. Further, a graph plotted on a three-dimensional rectangular coordinate system having R, G, and B axes as axes is projected from an RB component projected on a plane expressed by the following equation to determine an initially defined R value as a judgment value. As a result, the corroded portion (rust) and the hot-dip galvanized layer on the steel material surface can be easily distinguished. Further, from the RG component, the deterioration state of the hot-dip galvanized layer on the steel material surface can be evaluated and quantified. Embodiments of the present invention will be described below in detail. FIG. 2 is a diagram for evaluating the brightness of an image on a steel material surface.
FIG. 2 is a diagram in which a photograph (FIG. 2, point A) of a surface state of a steel material is partitioned by a lattice. The grid is also called a pixel (point B in FIG. 2) and represents the size and resolution of an image. The brightness (shade value) of the image at the position of each pixel is
It is called a gradation or a gradation value. In a gradation image, the image quality is higher as the number of gradations is larger. In the present invention, each pixel is represented by using three primary color signals of R (red), G (green), and B (blue) of the Munsell color system in a color image, and the gradation of the pixel is represented by R,
When 8 bits for each of G and B, that is, 2 8 = 256 steps, the number of colors that can be expressed with respect to the surface state of the steel material is 256
3 = 16777216 ≒ 16.8 million colors. Since the brightness of the color of a photograph varies depending on the photographing conditions, it is considered that the evaluation result is different between a photograph taken in an endoscope in a steel pipe and a photograph taken in the sun. . Therefore, by adjusting the color of the gray card imprinted on each photograph at the time of development, the colors are unified, the analog video signal of each pixel is spatially sampled, and A / D conversion is performed. It is taken into a computer as a digital video signal. At this time, since the error between the digital video signal and the analog video signal is reduced by making the sampling width as small as possible, the degree of deterioration of the steel material can be determined by the digital R, G, B signals as the digital video signal. And normalization is performed on (R ′, G ′, B ′) according to the following equation. In Equation 1, if n = 8, unified R ', G', and B 'can be expressed in 255 steps. The degree of deterioration of hot-dip galvanized steel is as follows:
From the test results such as the salt spray test in advance, FIG. 5 shows the structure diagram of the hot-dip galvanized film shown in FIG.
In the state where the layer (zinc layer) (FIG. 5, point E) remains, silver or gray is exhibited. II) The η layer is worn out, and the ζ layer (upper alloy layer) (FIG. 5, point F) becomes in the exposed state, exhibits brown or dark brown, with the III) zeta layer depletion and [delta] 1 layer (medium alloyed layer) (FIG. 5 G point) is exposed, exhibits a reddish brown to reddish brown or speckled, IV ) Δ 1 layer wears out, {layer (lower alloy layer) (FIG. 5, point H) is exposed, red-brown or spot-like red-brown, V)} layer wears out and steel material is exposed An evaluation standard value is set by quantitatively expressing that the state shows reddish brown. When the evaluation reference values are plotted on a three-dimensional rectangular coordinate system with R, G, and B as axes, R ′,
When G ′ and B ′ are represented by 255 levels, they are all plotted at fixed positions on a sphere having a radius of 255 as shown in FIG. R ', which unifies the brightness of the color in the deteriorated state
Degradation is achieved by plotting all the pixels in the image on the rectangular coordinates represented by G ′, B ′ and R, G, B as three axes and comparing them with the evaluation reference values shown in FIG. The distribution and spread of the state can be evaluated quantitatively, and differences in evaluation due to individual differences can be prevented. At this time, the smaller the pixel, the more accurately the state of the surface can be grasped. In the plot shown in FIG. 4, the darker color indicates the surface state of the steel material most. Further, the corrosion (rust) generated in the hot-dip galvanized steel material is a result of the cross-sectional defect progressing to the iron base beyond the layer Γ of the hot-dip galvanized film structure. The degradation state of R ',
G 'and B' have different colors. Therefore, the deterioration state is represented by R ', G', B ', and the result of plotting all the pixels in the image on the orthogonal coordinates with R, G, B as three axes is shown in the following equation. When projected on a plane and focusing only on the RG component, as shown in FIG. 5, the R value defined by the corrosion of the iron base is used as the judgment value, and the corroded portion (rust) on the steel material surface is determined by the RG coordinates. And the hot-dip galvanized layer can be easily distinguished. The RG coordinates can be quantitatively evaluated for the degree of deterioration of the hot-dip galvanized steel material by comparing it with an evaluation reference value that is quantitatively expressed in advance. Can be prevented. According to the present invention, the following effects can be obtained by performing the above-described procedure. The method according to claim 1, wherein the deterioration picture of the steel material subjected to the hot-dip galvanization is corrected and developed so that the color of the gray card imprinted at the time of photographing becomes R = G = B. , Using a scanner, etc., into the computer,
When performing image processing based on the G and B signals, the brightness (vector length) of a photograph taken under various conditions becomes a unified value, so that the degradation state independent of the photographing condition can be evaluated. . [0027] In the method of (2), the deterioration of the color of the steel in the deteriorated state is unified by subjecting the deterioration picture of the galvanized steel material to image processing according to the method described in (1). Values R ', G',
All the points in the image can be plotted using the resultant force expressed as a vector B ', and the distribution and spread of the deterioration state can be confirmed by easily comparing with a preset evaluation reference value. be able to. According to the method of the third aspect, the deterioration of the steel sheet subjected to the hot-dip galvanizing is determined according to the method described in the first aspect so that the evaluation of the photograph does not depend on the photographing state. R ', G', and B 'are represented by R, G, and B as three axes, and colors are represented by vectors in rectangular coordinates, projected onto a plane represented by the following equation (2), and only the RG component is used. It is possible to distinguish between corrosion (rust) of a steel material and a hot-dip galvanized layer, and to evaluate the degree of deterioration.
【図面の簡単な説明】
【図１】本発明による溶融亜鉛メッキを施した鋼材の劣
化状況の評価方法の説明するためのフローチャートであ
る。
【図２】鋼材の表面状態を撮影した写真を格子で仕切
り、各画素の分割の状態を表した図である。
【図３】溶融亜鉛メッキを施した鋼材の劣化状況写真か
ら、明るさを統一した値（Ｒ’，Ｇ’，Ｂ’）をプロッ
トする全ての半径が（２ｎ−１）の球を、３次元直角座
標系に表示した例である。
【図４】溶融亜鉛メッキを施した鋼材の劣化状況写真か
ら、劣化状態の色の明るさを基準化された値（Ｒ’，
Ｇ’，Ｂ’）でベクトル表示し、その合力を用いて画像
中の全ての点をプロットした例である。
【図５】溶融亜鉛メッキ皮膜の断面組織図である。
【図６】Ｒ＋Ｇ＋Ｂ＝１平面上のＲＧ成分図の例であ
る。
【符号の説明】
Ａ 写真
Ｂ １画素
Ｃ 横方向分割数
Ｄ 縦方向分割数
Ｅ 亜鉛層
Ｆ 上合金層
Ｇ 中合金層
Ｈ 下合金層
Ｉ 鉄地BRIEF DESCRIPTION OF THE DRAWINGS FIG. 1 is a flowchart for explaining a method for evaluating the deterioration state of a hot-dip galvanized steel material according to the present invention. FIG. 2 is a diagram showing a state in which each pixel is divided by dividing a photograph of the surface state of a steel material by a grid. FIG. 3 shows a sphere with all radii of (2 n -1) plotting values (R ′, G ′, B ′) in which brightness is unified from a deterioration state photograph of a hot-dip galvanized steel material. It is an example displayed on a three-dimensional rectangular coordinate system. FIG. 4 is a graph showing a deterioration state of a hot-dip galvanized steel material, and a value (R ′,
G ′, B ′), and all points in the image are plotted using the resultant force. FIG. 5 is a cross-sectional structure diagram of a hot-dip galvanized film. FIG. 6 is an example of an RG component diagram on a plane R + G + B = 1. [Description of References] A Photo B 1 pixel C Number of horizontal divisions D Number of vertical divisions E Zinc layer F Upper alloy layer G Medium alloy layer H Lower alloy layer I Iron base
Claims (1)
メッキを施した鋼材の劣化状況写真の明るさを統一する
ために、撮影時に解析対象物と同時に写し込んだグレイ
カードの色を、マンセル表色計の加法混色の３原則とし
て一般的なＲ（赤色），Ｇ（緑色），Ｂ（青色）を使用
し、Ｒ＝Ｇ＝Ｂとなるように色合いを補正，現像した
後、スキャナなどを用いて、鋼材の劣化状況写真のディ
ジタル映像信号を計算機に取り込み、鋼材表面の劣化状
況を色のＲ，Ｇ，Ｂ信号に分解して画像処理で表す場合
に、鋼材の劣化状況を任意の明るさ（ベクトル長さ）２
ｎ−１（ｎは任意数）に統一し、その値（Ｒ’，Ｇ’，
Ｂ’）を下記の式に代入して求め、撮影条件に依存しな
い評価ができることを特徴とする調査方法。 【数１】 【請求項２】 溶融亜鉛メッキを施した鋼材の劣化状
況写真を 【請求項１】のように補正，現像し、スキャナなどを用
いて計算機に取り込み、色のＲ，Ｇ，Ｂ信号に分解され
た画像処理結果から、任意位置での劣化状況を色のＲ，
Ｇ，Ｂ信号で表し、Ｒ，Ｇ，Ｂを３軸とする３次元直交
座標系に、劣化状態の色合いおよび明るさを統一化した
値（Ｒ’，Ｇ’，Ｂ’）でベクトル表示し、その合力を
用いて画像中の全ての点をプロットすることにより、予
め設定しておいた劣化度と簡単に比較でき、劣化状態の
分布や広がりを確認することを特徴とする調査方法。 【請求項３】 溶融亜鉛メッキを施した鋼材の写真
を、撮影状況に評価が依存しないように、 【請求項１】で示す方法で任意位置の劣化状況をＲ’，
Ｇ’，Ｂ’で表し、Ｒ，Ｇ，Ｂを３軸とする３次元直交
座標系にベクトル表示し、下記の式で示す平面に投影し
て、そのＲＧ成分のみ使用することで、鋼材の腐食
（錆）と溶融亜鉛メッキ層の区別および、劣化度の評価
ができることを特徴とする調査方法。 【数２】 (57) [Claims] [Claim 1] In order to unify the brightness of the deterioration picture of the hot-dip galvanized steel material taken under various conditions, at the same time as the object to be analyzed at the time of shooting Using the general R (red), G (green), and B (blue) as the three principles of the additive color mixture of the Munsell colorimeter, the color of the printed gray card is set so that R = G = B. After correcting and developing the color tone, using a scanner or the like, the digital image signal of the photograph of the deterioration state of the steel material is taken into a computer, and the deterioration state of the steel material surface is decomposed into R, G, and B signals of colors and represented by image processing. In the case, the deterioration state of the steel material is determined by an arbitrary brightness (vector length) 2
n- 1 (n is an arbitrary number), and the values (R ', G',
B ') by substituting B') into the following equation, and performing evaluation independent of imaging conditions. (Equation 1) 2. A deterioration picture of a steel material subjected to hot-dip galvanizing is corrected, developed and taken into a computer using a scanner as described in [1], and is decomposed into R, G, B signals of colors. From the image processing results obtained, the degradation status at an arbitrary position is indicated by the R,
G and B signals are displayed in a three-dimensional rectangular coordinate system with R, G and B as three axes, and vectors and values (R ', G' and B ') in which the color and brightness of the deteriorated state are unified are displayed. A method of plotting all points in an image using the resultant force to easily compare the degree of deterioration with a preset degree, and confirming the distribution and spread of the state of deterioration. 3. The method of claim 1, wherein a photograph of the steel material subjected to hot-dip galvanizing is degraded by R ′,
G ′, B ′, expressed as a vector in a three-dimensional orthogonal coordinate system having R, G, and B as three axes, projected onto a plane represented by the following equation, and using only the RG component thereof, An investigation method characterized by the ability to distinguish between corrosion (rust) and hot-dip galvanized layers and to evaluate the degree of deterioration. (Equation 2)
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| JP9228800A JP3013301B2 (en) | 1997-07-22 | 1997-07-22 | Degradation evaluation method of steel surface using image processing |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| JP9228800A JP3013301B2 (en) | 1997-07-22 | 1997-07-22 | Degradation evaluation method of steel surface using image processing |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| JPH1137950A JPH1137950A (en) | 1999-02-12 |
| JP3013301B2 true JP3013301B2 (en) | 2000-02-28 |
Family
ID=16882061
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|---|---|---|---|
| JP9228800A Expired - Fee Related JP3013301B2 (en) | 1997-07-22 | 1997-07-22 | Degradation evaluation method of steel surface using image processing |
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| Country | Link |
|---|---|
| JP (1) | JP3013301B2 (en) |
Families Citing this family (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2003222587A (en) * | 2001-11-20 | 2003-08-08 | Hitachi Ltd | Non-destructive degradation diagnosis method and its diagnostic device |
| JP4116926B2 (en) * | 2003-05-27 | 2008-07-09 | 善文 安岡 | Spectral imaging device |
| JP4955411B2 (en) * | 2007-01-31 | 2012-06-20 | 太陽工業株式会社 | Determination apparatus, determination system, determination method, and computer program |
| JP5647878B2 (en) * | 2010-05-31 | 2015-01-07 | 東北電力株式会社 | Steel pipe internal corrosion analysis apparatus and steel pipe internal corrosion analysis method |
| JP6201922B2 (en) * | 2014-07-23 | 2017-09-27 | マツダ株式会社 | Rust detection device for vehicle, rust detection system for vehicle, and rust detection method for vehicle |
| CN119027418B (en) * | 2024-10-28 | 2025-01-24 | 山东乾钢金属科技有限公司 | Image processing method based on strip steel surface detection |
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