A new method for automatic separation of fabric color

A novel method combining the characteristics of structure and region information is proposed for automatic segmentation of the color region for different kinds of fabrics. For improving image quality for computer analysis, the structure-texture decomposition processing has been used to extract the main structure from the fabric image, where the fine structure details of fabric yarn patterns have been removed. By using the CIE-Lab color system, the color structure image is then segmented by a fuzzy region-based segmentation model that can be solved efficiently through a fast numerical scheme. The experimental results show that the main disadvantage and difficulty of using color clustering-based methods and commonly used image segmentation methods for fabric color separation is overcome by the proposed method. The proposed method has high accuracy and the computation time is very reasonable. It can be applied to extract fabric color regions for different fabric structures, such as woven, knitted and embroidery structures.

[1]  Yu Han,et al.  Design through cognitive color theme: A new approach for fabric design , 2012, 2012 IEEE 11th International Conference on Cognitive Informatics and Cognitive Computing.

[2]  Michael K. Ng,et al.  A Fast Total Variation Minimization Method for Image Restoration , 2008, Multiscale Model. Simul..

[3]  Dani Lischinski,et al.  Colorization using optimization , 2004, ACM Trans. Graph..

[4]  Ali S. Hadi,et al.  Finding Groups in Data: An Introduction to Chster Analysis , 1991 .

[5]  Chih-Yuan Kao,et al.  Self-organizing map network for automatically recognizing color texture fabric nature , 2007 .

[6]  Michael K. Ng,et al.  A Multiphase Image Segmentation Method Based on Fuzzy Region Competition , 2010, SIAM J. Imaging Sci..

[7]  J. MacQueen.  Some methods for classification and analysis of multivariate observations , 1967 .

[8]  Tony F. Chan,et al.  Active contours without edges , 2001, IEEE Trans. Image Process..

[9]  Tony F. Chan,et al.  Structure-Texture Image Decomposition—Modeling, Algorithms, and Parameter Selection , 2006, International Journal of Computer Vision.

[10]  Chung-Feng Jeffrey Kuo,et al.  Automatic Recognition of Fabric Nature by Using the Approach of Texture Analysis , 2006 .

[11]  Bugao Xu,et al.  Identifying Fabric Structures with Fast Fourier Transform Techniques , 1996 .

[12]  Hossein Mobahi,et al.  Natural Image Segmentation with Adaptive Texture and Boundary Encoding , 2009, ACCV.

[13]  Xiangchu Feng,et al.  A new fast multiphase image segmentation algorithm based on nonconvex regularizer , 2012, Pattern Recognit..

[14]  Jihong Liu,et al.  Automatic Detection of the Layout of Color Yarns for Yarn-dyed Fabric via a FCM Algorithm , 2010 .

[15]  Allen Y. Yang,et al.  Unsupervised segmentation of natural images via lossy data compression , 2008, Comput. Vis. Image Underst..

[16]  Lapo Governi,et al.  The recycling of wool clothes: an artificial neural network colour classification tool , 2008 .

[17]  Josef Kittler,et al.  Histogram-based segmentation in a perceptually uniform color space , 1998, IEEE Trans. Image Process..

[18]  Chung-Yang Shih,et al.  Automatic Recognition of Fabric Weave Patterns by a Fuzzy C-Means Clustering Method , 2004 .

[19]  Dorin Comaniciu,et al.  Mean Shift: A Robust Approach Toward Feature Space Analysis , 2002, IEEE Trans. Pattern Anal. Mach. Intell..

[20]  Xiangchu Feng,et al.  Fuzzy region competition-based auto-color-theme design for textile images , 2013 .

[21]  Dejun Zheng.  A new method for the detection and classification of weave pattern repeat , 2014 .

[22]  Xiangchu Feng,et al.  Variational and PCA based natural image segmentation , 2013, Pattern Recognit..

[23]  ANTONIN CHAMBOLLE,et al.  An Algorithm for Total Variation Minimization and Applications , 2004, Journal of Mathematical Imaging and Vision.

[24]  Liangliang Cao,et al.  Image Segmentation by MAP-ML Estimations , 2010, IEEE Transactions on Image Processing.

[25]  Dejun Zheng,et al.  A new method for classification of woven structure for yarn-dyed fabric , 2014 .

[26]  Jitendra Malik,et al.  Blobworld: Image Segmentation Using Expectation-Maximization and Its Application to Image Querying , 2002, IEEE Trans. Pattern Anal. Mach. Intell..

[27]  Li Xu,et al.  Structure extraction from texture via relative total variation , 2012, ACM Trans. Graph..

[28]  R. Keys.  Cubic convolution interpolation for digital image processing , 1981 .

[29]  P. Lions,et al.  Image recovery via total variation minimization and related problems , 1997 .

[30]  George Baciu,et al.  Investigation on the Classification of Weave Pattern Based on an Active Grid Model , 2009 .

[31]  Jeng-Jong Lin.  Applying a Co-occurrence Matrix to Automatic Inspection of Weaving Density for Woven Fabrics , 2002 .

[32]  Roberto Manduchi,et al.  Bilateral filtering for gray and color images , 1998, Sixth International Conference on Computer Vision (IEEE Cat. No.98CH36271).

[33]  Errol J. Wood,et al.  Applying Fourier and Associated Transforms to Pattern Characterization in Textiles , 1990 .

[34]  J Escofet,et al.  Fourier domain based angular correlation for quasiperiodic pattern recognition. Hybrid architecture , 1998 .

[35]  Richard Szeliski,et al.  Multigrid and multilevel preconditioners for computational photography , 2011, ACM Trans. Graph..

[36]  Chung-Feng Jeffrey Kuo,et al.  Automatic machine embroidery image color analysis system. Part I: Using Gustafson-Kessel clustering algorithm in embroidery fabric color separation , 2012 .

[37]  Jihong Liu,et al.  Measuring linear density of threads in single-system-mélange color fabrics with FCM algorithm , 2012 .