基于切面投影图像的织物起球等级的计算机视觉评定
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摘要
本文对基于切面光照投影图像的织物起球等级的计算机视觉评定进行了系统地研究。论文内容涉及序列切面投影图像采集装置的设计和研制，织物起球表面切面投影轮廓线的提取以及由拼接序列切面投影轮廓线而获取织物三维起球图像的途径、织物起球图像预处理和毛球分割的算法及效果、织物起球的特征提取；以及应用神经网络对织物起球等级的评定等。现将论文各章内容简要介绍如下：
引言部分简要介绍了论文的选题背景。
第一章概述了国内外有关基于计算机视觉的织物起球等级评定的研究现状。除对织物起球实验和起球等级的主观评定方法作一般介绍外，着重从灰度图像分析和距离图像分析二方面介绍了国内外基于计算机视觉的织物起球等级评定的新研究成果及其不足之处。
第二章介绍了织物序列切面投影图像采集装置的研制，讨论了关键零件异型杆的设计。文中从理论上分析了异型杆边缘曲率半径和毛球半径之比对织物起球图像中毛球的伸缩变形和“粘连”的影响，从而为异型杆半径设计提供了依据。文中还从结构设计和刚度方面讨论了异型杆的正确截面形状。
第三章详细介绍了如何利用织物序列切面投影图像获取织物起球图像的理论、方法和途径。文中介绍了如何正确确定切面投影图像采集时的背景光强，还系统介绍了利用LOG边缘检测算子和插值法提取起球织物切面投影轮廓线的途径，和通过拼接序列切面投影轮廓线得到织物三维起球图像及其二维灰度显示的方法。文中着重指出，这种基于序列切面投影图像的织物起球图像获取方法可避免织物纹理、色彩等对织物起球信息的影响，从而使本文的起球评定方法不仅适用于素色织物，也适用于色织物、印花织物及其它花式织物。
第四章详细讨论了织物起球图像的预处理和毛球分割。文中详细论
述了织物起球图像中背景不匀的来源和毛球孔洞存在的原因以及应用形
态学方法逐步有序的进行消除的过程。文中介绍了四种阂值方法分割毛
球的结果，并着重论述了用高斯拟合闭值法分割毛球的合理性和可行性，
文中还提供了对印花织物、色织物、素色织物等不同类型织物、不同等
级试样的起球图像进行毛球分割的结果。
第五章介绍了起球图像特征值的提取，并详细分析了粗糙度、偏度、
毛球个数、毛球平均高度、毛球最大高度、毛球总体积、毛球总面积、
毛球平均面积和毛球分形维等特征值与起球等级的相关性和类别可分
性，从而为起球等级评定提供了依据。
第六章介绍了用100个起球织物试样对Bp网络和自组织神经网络进
行训练和测试的过程以及网络的评定结果。Bp网络评定结果与主观评定
结果的相关系数是0.97，等级评定的正确率是92%;自组织神经网络的
评定结果与主观评定结果的相关系数是0.95，等级评定的正确率是84%。
文中还对这两种网络的性能及应用进行了分析比较。
第七章对全文进行了总结。介绍了本文的主要贡献和存在的问题，
对进一步研究方向提出了建议。
The objective evaluation of fabric pilling grade based on tangential light projected image using computer vision is studied in this thesis. The main contents covered by the thesis are the design and installation of the device for capturing light projected images, the extraction of the tangential projected profile of pilled fabric surface and the development of 3-D image of pilled fabric from the integration of sequential tangential projected profile, the algorithm and results of the image preprocessing and pill segmentation, the extraction of pill's feature index, the assessment of pilling grade by neural network, and etc. The following is a brief introduction of the content for each chapter.
In foreword the background of topic selection of this thesis is described briefly.
In chapter 1 a brief account of the recent progress in the world of studies on the evaluation of pilling grade using computer vision is presented. In addition to the general description of the method of pilling testing and the subjective evaluation of pilling grade, the new results and deficiency of the objective evaluation of pilling grade using computer vision, which is explained by both the gray image analysis and range image analysis, are given out emphatically.
In chapter 2 the development of the device for capturing the projected images and the design of shaped bar which is the key part of the device, are discussed. And it is also analyzed in detail that on the images of pilled fabrics how the ratio of the edge curvature radius of shaped bar to pills radius affects the distortion of pills either extension or shorten and the conglutination of pills, ie, the projected image of more than one pills superimposed along the lines of sample moving forward. The cross-sectional figure of shaped bar is considered properly according to the requirements of both structure and rigidity.
In chapter 3 the development of pilling images of pilled fabric samples based on tangential light projected images is elaborated. The main contents include as follows: the investigation of background light intensity for capturing the projected images with proper contrast, the detection of the tangential projected profile of pilled fabric surface using edge detection of LOG operator and liner interpolation, the acquiring of the 3-D image of pilled fabric by integrating sequential projected profiles, the 2-D gray display of the 3-D image and etc. The method of acquiring the pilling image of fabric samples described in this chapter can eliminate the interference with pilling information from fabric color and pattern, and therefore can be applied to not only solid colored fabric, but also colored woven fabric, printed fabric and other fancy fabric.
In chapter 4 the image preprocessing and pill segmentation are discussed. The background unevenness and the pill's gap on pilling images of pilled fabric are analyzed and their removals using operation of mathematical morphology and other method are introduced in detail. Four different kinds of threshold are used to segment the pills on pilling images. Besides showing all the results, the emphasis is put on the analysis of the reasonableness and feasibility of pill segmentation by threshold based on Gaussian model. Finally, the results of pill segmentation with reference to the pilling images of solid color fabric and especially colored and printed fabric by the threshold based on Gaussian model are provided.
In chapter 5 the extraction of pill's feature indexes, such as roughness, number of pills, total area of pills, fractal dimension of pills, is introduced. The correlation between each feature index and pilling grade and the separability of each index are analyzed particularly, which provides the foundation of assessing pilling grade.
In chapter 6 the training and testing process of Bp network and SOFM network using 100 fabric samples, and the assessed results of pilling grade by neural network are presented. The correlation between pilling grade assessed by Bp network and that by skilled person is 0.97, and
引言部分简要介绍了论文的选题背景。
第一章概述了国内外有关基于计算机视觉的织物起球等级评定的研究现状。除对织物起球实验和起球等级的主观评定方法作一般介绍外，着重从灰度图像分析和距离图像分析二方面介绍了国内外基于计算机视觉的织物起球等级评定的新研究成果及其不足之处。
第二章介绍了织物序列切面投影图像采集装置的研制，讨论了关键零件异型杆的设计。文中从理论上分析了异型杆边缘曲率半径和毛球半径之比对织物起球图像中毛球的伸缩变形和“粘连”的影响，从而为异型杆半径设计提供了依据。文中还从结构设计和刚度方面讨论了异型杆的正确截面形状。
第三章详细介绍了如何利用织物序列切面投影图像获取织物起球图像的理论、方法和途径。文中介绍了如何正确确定切面投影图像采集时的背景光强，还系统介绍了利用LOG边缘检测算子和插值法提取起球织物切面投影轮廓线的途径，和通过拼接序列切面投影轮廓线得到织物三维起球图像及其二维灰度显示的方法。文中着重指出，这种基于序列切面投影图像的织物起球图像获取方法可避免织物纹理、色彩等对织物起球信息的影响，从而使本文的起球评定方法不仅适用于素色织物，也适用于色织物、印花织物及其它花式织物。
第四章详细讨论了织物起球图像的预处理和毛球分割。文中详细论
述了织物起球图像中背景不匀的来源和毛球孔洞存在的原因以及应用形
态学方法逐步有序的进行消除的过程。文中介绍了四种阂值方法分割毛
球的结果，并着重论述了用高斯拟合闭值法分割毛球的合理性和可行性，
文中还提供了对印花织物、色织物、素色织物等不同类型织物、不同等
级试样的起球图像进行毛球分割的结果。
第五章介绍了起球图像特征值的提取，并详细分析了粗糙度、偏度、
毛球个数、毛球平均高度、毛球最大高度、毛球总体积、毛球总面积、
毛球平均面积和毛球分形维等特征值与起球等级的相关性和类别可分
性，从而为起球等级评定提供了依据。
第六章介绍了用100个起球织物试样对Bp网络和自组织神经网络进
行训练和测试的过程以及网络的评定结果。Bp网络评定结果与主观评定
结果的相关系数是0.97，等级评定的正确率是92%;自组织神经网络的
评定结果与主观评定结果的相关系数是0.95，等级评定的正确率是84%。
文中还对这两种网络的性能及应用进行了分析比较。
第七章对全文进行了总结。介绍了本文的主要贡献和存在的问题，
对进一步研究方向提出了建议。
The objective evaluation of fabric pilling grade based on tangential light projected image using computer vision is studied in this thesis. The main contents covered by the thesis are the design and installation of the device for capturing light projected images, the extraction of the tangential projected profile of pilled fabric surface and the development of 3-D image of pilled fabric from the integration of sequential tangential projected profile, the algorithm and results of the image preprocessing and pill segmentation, the extraction of pill's feature index, the assessment of pilling grade by neural network, and etc. The following is a brief introduction of the content for each chapter.
In foreword the background of topic selection of this thesis is described briefly.
In chapter 1 a brief account of the recent progress in the world of studies on the evaluation of pilling grade using computer vision is presented. In addition to the general description of the method of pilling testing and the subjective evaluation of pilling grade, the new results and deficiency of the objective evaluation of pilling grade using computer vision, which is explained by both the gray image analysis and range image analysis, are given out emphatically.
In chapter 2 the development of the device for capturing the projected images and the design of shaped bar which is the key part of the device, are discussed. And it is also analyzed in detail that on the images of pilled fabrics how the ratio of the edge curvature radius of shaped bar to pills radius affects the distortion of pills either extension or shorten and the conglutination of pills, ie, the projected image of more than one pills superimposed along the lines of sample moving forward. The cross-sectional figure of shaped bar is considered properly according to the requirements of both structure and rigidity.
In chapter 3 the development of pilling images of pilled fabric samples based on tangential light projected images is elaborated. The main contents include as follows: the investigation of background light intensity for capturing the projected images with proper contrast, the detection of the tangential projected profile of pilled fabric surface using edge detection of LOG operator and liner interpolation, the acquiring of the 3-D image of pilled fabric by integrating sequential projected profiles, the 2-D gray display of the 3-D image and etc. The method of acquiring the pilling image of fabric samples described in this chapter can eliminate the interference with pilling information from fabric color and pattern, and therefore can be applied to not only solid colored fabric, but also colored woven fabric, printed fabric and other fancy fabric.
In chapter 4 the image preprocessing and pill segmentation are discussed. The background unevenness and the pill's gap on pilling images of pilled fabric are analyzed and their removals using operation of mathematical morphology and other method are introduced in detail. Four different kinds of threshold are used to segment the pills on pilling images. Besides showing all the results, the emphasis is put on the analysis of the reasonableness and feasibility of pill segmentation by threshold based on Gaussian model. Finally, the results of pill segmentation with reference to the pilling images of solid color fabric and especially colored and printed fabric by the threshold based on Gaussian model are provided.
In chapter 5 the extraction of pill's feature indexes, such as roughness, number of pills, total area of pills, fractal dimension of pills, is introduced. The correlation between each feature index and pilling grade and the separability of each index are analyzed particularly, which provides the foundation of assessing pilling grade.
In chapter 6 the training and testing process of Bp network and SOFM network using 100 fabric samples, and the assessed results of pilling grade by neural network are presented. The correlation between pilling grade assessed by Bp network and that by skilled person is 0.97, and
引文
[1] Goktepe O., Fabric Pilling Performance and Sensitivity of Several Pilling Testers, Textile Research Journal, 2002, 72(7), 625-630
[2] Biermann I., Pilling Tendencies of Textiles -- Special Features of Measurement and Assessment, Melliand Textilberichte/International Textile Reports, 2001, 82(4), 300-302, E83-84
[3] Abrasion and Wear, Textile Testing and Analysis, 1999,127-156
[4] Sirikasemlert A., Tao X., Dhingra R. C., Superficial Performance, Textile Asia, 1996, 28(3), 73-76
[5] Nitschke W., Comparative Study of Pilling Testing, Melliand Textilberichte/International Textile Reports, 1995, 76(9), 624-626, E161-162
[6] Naylor G. R. S., Williams V. A. Laboratory Evaluation of the Pilling Performance of Worsted-Spun Wool Knitwear, Proceedings of the 9th International Wool Textile Research Conference -- Material Specification - New Products and Product Development, 1995, 139-143
[7] Abrasion and Pilling Tester, Knitting Technique, 1994, 16(2), 110
[8] Textile Wear Resistance--a Half Century of Abrasion Testing, Textile Horizons, 1992,12(10), 83-84
[9] Photographic Stands for Evaluation the Pilling Process, Melliand Textilberichte/International Textile Reports, 1991, 72(7), 517, E221
[10] Fiber Attrition in the Atlas Random Tumble Pilling Tester as a Measure of Abrasion-resistance in Knitted Wool Fabrics, Journal of the Textile Institute, 1989, 80(4), 611-613
[11] Paek S. L., Pilling, Abrasion, and Tensile Properties of Fabrics from Open-end and Spun yarns, Textile Research Journal, 1989, 59(10), 577-583
[12] Cooke W. D., Goeksoy M., Problem of Predicting Pilling Performance Using Laboratory Test Methods, Melliand Textilberichte/International Textile Reports, 1988, 69(4), 250-254, E134-E135
[13] Trankle G., Schrobsdorff B., Tendency to Pilling of Knitgoods, Melliand Textilberichte-International Textile Reports, 1983, 12(5), 332-335
[14] 中华人民共和国国家标准，织物起球试验方法，GB4802．1－4802．3－84
[15] Millan M. S., Abril H. C., Image Analysis of Standard Pilling Series, Optical Engineering, 2001,40(7), 1281-1286
[16] Neilly D. J, Grades of Pilling, Textile Asia, 1990, 21(3), 68-69
[17] Konda A,Xin L.C,etc, Evaluation of Pilling by Computer Image Analysis, Journal of the textile Machinery Society of Japan, 1990, 36(3), 96-107
[18] Hsi.H.C, Bresee R.R and Annis P.A, Characterizing Fabric Pilling by Using Image-analysis Techniques Part Ⅰ: Pill Detection and Description, Journal of the Textile Institute. 1998, 89(1), 80-95
[19] Hsi.H.C, Bresee R.R and Annis P.A, Characterizing Fabric Pilling by Using Image-analysis Techniques Part Ⅱ: Comparison with Visual Pill Rating, Journal of the Textile Institute. 1998, 89(1), 96-105
[20] Hsi.H.C, Bresee R.R., Pilling Evaluation of Laboratory, Abraded, Laundered and Worn Fabrics Using Image Analysis, AATCC, book ofpapers, 1996, 465-479
[21] Xu B, Instrumental Evaluation of Fabric Pilling, Journal of the Textile Institute, 1997, 88(4), 488-500
[22] Xu B, Instrumental Evaluation of Fabric Pilling, AATCC, book of papers, 1996, 380-392
[23] Abril H.C.,Millan M.S, Torres Y, Navarro R, Automatic method based on image analysis for pilling evaluation in fabrics, Optical Engineer, 1998, 37(11), 2937-2947,
[24] Abril H.C, Millan M.S, Torres Y, Objective automatic assessment of pilling in fabrics by image analysis, Optical Engineer, 2000, 39(6), 1477-1488
[25] Abril H.C., Torres Y., Millan M.S, Image Synthesis of Pilled Textiles by Karhunen-Loeve Transform, SPIE, 1999, 3572, 254-258
[26] Millan M. S., Escofet J., etc, Automatic quality control of textile webs by image processing, SPIE, 1999, 3572, 349-352
[27] Abril H.C, Millan M.S, Torres Y and Navarro R, Image Segmentation based on a Gaussian Model appllied to pilling evaluation in fabrics, Proc.SPIE, 1997, 3101,283-291
[28] Kim H. S., Pourdeyhimi B., Latifi M., Characterizing Fabric Pilling due to Fabric-to-fabric Abrasion, Textile Research Journal, 2001, 71 (7), 640-644
[29] Fazekas Z., Komuves J., etc, Automatic Visual Assessment of Fabric Quality, ISIE'99: Proceedings of the IEEE International Symposium on Industrial Electronics, 178-182
[30] Ramgulam R.B, Amirbayat J and Porat Ⅰ, The Objective Assessment of Fabric Pilling Part Ⅰ:Methodology, Journal of the Textile Institute, 1993, 84(2), 221-226
[31] Ramgulam R.B, Amirbayat J and Porat Ⅰ, The Objective Assessment of Fabric Pilling Part Ⅱ:Experimental Work, Journal of the Textile Institute, 1993, 84(2), 397-401
[32] Sirikasemlert A and Tao X, Objective Evaluation of Textural Changes in Knitted Fabrics by Laser Triangulation, Textile Research Journal, 2000(12), 70, 1076-1087
[33] 徐增波，应用图像分析技术评估织物起球等级，中国纺织大学学报，1999，3，28-33
[33] 史广安，刘兵等，纺织学报，1997，(5)，36-37，
[34] 何曼娜，绒线织物起球的计算机图像分析评估，中国纺织大学论文，1998
[35] 王晓红， 图像分析技术评价织物起球，纺织学报，1998，12，9－11，
[36]] 王晓红， 应用图像处理技术评价织物起球等级，纺织学报，1999，6，24－26，
[2] Biermann I., Pilling Tendencies of Textiles -- Special Features of Measurement and Assessment, Melliand Textilberichte/International Textile Reports, 2001, 82(4), 300-302, E83-84
[3] Abrasion and Wear, Textile Testing and Analysis, 1999,127-156
[4] Sirikasemlert A., Tao X., Dhingra R. C., Superficial Performance, Textile Asia, 1996, 28(3), 73-76
[5] Nitschke W., Comparative Study of Pilling Testing, Melliand Textilberichte/International Textile Reports, 1995, 76(9), 624-626, E161-162
[6] Naylor G. R. S., Williams V. A. Laboratory Evaluation of the Pilling Performance of Worsted-Spun Wool Knitwear, Proceedings of the 9th International Wool Textile Research Conference -- Material Specification - New Products and Product Development, 1995, 139-143
[7] Abrasion and Pilling Tester, Knitting Technique, 1994, 16(2), 110
[8] Textile Wear Resistance--a Half Century of Abrasion Testing, Textile Horizons, 1992,12(10), 83-84
[9] Photographic Stands for Evaluation the Pilling Process, Melliand Textilberichte/International Textile Reports, 1991, 72(7), 517, E221
[10] Fiber Attrition in the Atlas Random Tumble Pilling Tester as a Measure of Abrasion-resistance in Knitted Wool Fabrics, Journal of the Textile Institute, 1989, 80(4), 611-613
[11] Paek S. L., Pilling, Abrasion, and Tensile Properties of Fabrics from Open-end and Spun yarns, Textile Research Journal, 1989, 59(10), 577-583
[12] Cooke W. D., Goeksoy M., Problem of Predicting Pilling Performance Using Laboratory Test Methods, Melliand Textilberichte/International Textile Reports, 1988, 69(4), 250-254, E134-E135
[13] Trankle G., Schrobsdorff B., Tendency to Pilling of Knitgoods, Melliand Textilberichte-International Textile Reports, 1983, 12(5), 332-335
[14] 中华人民共和国国家标准，织物起球试验方法，GB4802．1－4802．3－84
[15] Millan M. S., Abril H. C., Image Analysis of Standard Pilling Series, Optical Engineering, 2001,40(7), 1281-1286
[16] Neilly D. J, Grades of Pilling, Textile Asia, 1990, 21(3), 68-69
[17] Konda A,Xin L.C,etc, Evaluation of Pilling by Computer Image Analysis, Journal of the textile Machinery Society of Japan, 1990, 36(3), 96-107
[18] Hsi.H.C, Bresee R.R and Annis P.A, Characterizing Fabric Pilling by Using Image-analysis Techniques Part Ⅰ: Pill Detection and Description, Journal of the Textile Institute. 1998, 89(1), 80-95
[19] Hsi.H.C, Bresee R.R and Annis P.A, Characterizing Fabric Pilling by Using Image-analysis Techniques Part Ⅱ: Comparison with Visual Pill Rating, Journal of the Textile Institute. 1998, 89(1), 96-105
[20] Hsi.H.C, Bresee R.R., Pilling Evaluation of Laboratory, Abraded, Laundered and Worn Fabrics Using Image Analysis, AATCC, book ofpapers, 1996, 465-479
[21] Xu B, Instrumental Evaluation of Fabric Pilling, Journal of the Textile Institute, 1997, 88(4), 488-500
[22] Xu B, Instrumental Evaluation of Fabric Pilling, AATCC, book of papers, 1996, 380-392
[23] Abril H.C.,Millan M.S, Torres Y, Navarro R, Automatic method based on image analysis for pilling evaluation in fabrics, Optical Engineer, 1998, 37(11), 2937-2947,
[24] Abril H.C, Millan M.S, Torres Y, Objective automatic assessment of pilling in fabrics by image analysis, Optical Engineer, 2000, 39(6), 1477-1488
[25] Abril H.C., Torres Y., Millan M.S, Image Synthesis of Pilled Textiles by Karhunen-Loeve Transform, SPIE, 1999, 3572, 254-258
[26] Millan M. S., Escofet J., etc, Automatic quality control of textile webs by image processing, SPIE, 1999, 3572, 349-352
[27] Abril H.C, Millan M.S, Torres Y and Navarro R, Image Segmentation based on a Gaussian Model appllied to pilling evaluation in fabrics, Proc.SPIE, 1997, 3101,283-291
[28] Kim H. S., Pourdeyhimi B., Latifi M., Characterizing Fabric Pilling due to Fabric-to-fabric Abrasion, Textile Research Journal, 2001, 71 (7), 640-644
[29] Fazekas Z., Komuves J., etc, Automatic Visual Assessment of Fabric Quality, ISIE'99: Proceedings of the IEEE International Symposium on Industrial Electronics, 178-182
[30] Ramgulam R.B, Amirbayat J and Porat Ⅰ, The Objective Assessment of Fabric Pilling Part Ⅰ:Methodology, Journal of the Textile Institute, 1993, 84(2), 221-226
[31] Ramgulam R.B, Amirbayat J and Porat Ⅰ, The Objective Assessment of Fabric Pilling Part Ⅱ:Experimental Work, Journal of the Textile Institute, 1993, 84(2), 397-401
[32] Sirikasemlert A and Tao X, Objective Evaluation of Textural Changes in Knitted Fabrics by Laser Triangulation, Textile Research Journal, 2000(12), 70, 1076-1087
[33] 徐增波，应用图像分析技术评估织物起球等级，中国纺织大学学报，1999，3，28-33
[33] 史广安，刘兵等，纺织学报，1997，(5)，36-37，
[34] 何曼娜，绒线织物起球的计算机图像分析评估，中国纺织大学论文，1998
[35] 王晓红， 图像分析技术评价织物起球，纺织学报，1998，12，9－11，
[36]] 王晓红， 应用图像处理技术评价织物起球等级，纺织学报，1999，6，24－26，