Ciratefi: An RST-invariant template matching with extension to color images

Template matching is a technique widely used for finding patterns in digital images. A good template matching should be able to detect template instances that have undergone geometric transformations. In this paper, we proposed a grayscale template matching algorithm named Ciratefi, invariant to rotation, scale, translation, brightness and contrast and its extension to color images. We introduce CSSIM (color structural similarity) for comparing the similarity of two color image patches and use it in our algorithm. We also describe a scheme to determine automatically the appropriate parameters of our algorithm and use pyramidal structure to improve the scale invariance. We conducted several experiments to compare grayscale and color Ciratefis with SIFT, C-color-SIFT and EasyMatch algorithms in many different situations. The results attest that grayscale and color Ciratefis are more accurate than the compared algorithms and that color-Ciratefi outperforms grayscale Ciratefi most of the time. However, Ciratefi is slower than the other algorithms.

[1]  Hae Yong Kim.  Rotation-discriminating template matching based on Fourier coefficients of radial projections with robustness to scaling and partial occlusion , 2010, Pattern Recognit..

[2]  Du-Ming Tsai,et al.  Rotation-invariant pattern matching with color ring-projection , 2002, Pattern Recognit..

[3]  Touradj Ebrahimi,et al.  Efficient Rotation-Discriminative Template Matching , 2007, CIARP.

[4]  Luc Van Gool,et al.  SURF: Speeded Up Robust Features , 2006, ECCV.

[5]  Cordelia Schmid,et al.  A performance evaluation of local descriptors , 2005, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[6]  Brian V. Funt,et al.  Is Machine Colour Constancy Good Enough? , 1998, ECCV.

[7]  Hae Yong Kim,et al.  Automatic VHDL generation for solving rotation and scale-invariant template matching in FPGA , 2009, 2009 5th Southern Conference on Programmable Logic (SPL).

[8]  Yehezkel Lamdan,et al.  Geometric Hashing: A General And Efficient Model-based Recognition Scheme , 1988, [1988 Proceedings] Second International Conference on Computer Vision.

[9]  Farzin Mokhtarian,et al.  A Theory of Multiscale, Curvature-Based Shape Representation for Planar Curves , 1992, IEEE Trans. Pattern Anal. Mach. Intell..

[10]  Aly A. Farag,et al.  CSIFT: A SIFT Descriptor with Color Invariant Characteristics , 2006, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06).

[11]  Gertjan J. Burghouts,et al.  Performance evaluation of local colour invariants , 2009, Comput. Vis. Image Underst..

[12]  Theo Gevers,et al.  A Perceptual Comparison of Distance Measures for Color Constancy Algorithms , 2008, ECCV.

[13]  Hae Yong Kim,et al.  Color-Ciratefi: A color-based RST-invariant template matching algorithm , 2010 .

[14]  Michel Defrise,et al.  Symmetric Phase-Only Matched Filtering of Fourier-Mellin Transforms for Image Registration and Recognition , 1994, IEEE Trans. Pattern Anal. Mach. Intell..

[15]  Gerald Schaefer.  How Useful are Colour Invariants for Image Retrieval? , 2004, ICCVG.

[16]  Frédéric Jurie,et al.  Learned color constancy from local correspondences , 2005, 2005 IEEE International Conference on Multimedia and Expo.

[17]  Arnold W. M. Smeulders,et al.  The Amsterdam Library of Object Images , 2004, International Journal of Computer Vision.

[18]  Stefanos D. Kollias,et al.  A visual pathway for shape-based invariant classification of gray scale images , 2007, Integr. Comput. Aided Eng..

[19]  Arnold W. M. Smeulders,et al.  Color Invariance , 2001, IEEE Trans. Pattern Anal. Mach. Intell..

[20]  Dana H. Ballard,et al.  Generalizing the Hough transform to detect arbitrary shapes , 1981, Pattern Recognit..

[21]  J. P. Lewis.  Fast Normalized Cross-Correlation , 2010 .

[22]  Eero P. Simoncelli,et al.  Image quality assessment: from error visibility to structural similarity , 2004, IEEE Transactions on Image Processing.

[23]  Hae Yong Kim,et al.  Grayscale Template-Matching Invariant to Rotation, Scale, Translation, Brightness and Contrast , 2007, PSIVT.

[24]  Wanlei Zhou,et al.  Spectral shape descriptor using spherical harmonics , 2010, Integr. Comput. Aided Eng..

[25]  Koen E. A. van de Sande,et al.  Evaluating Color Descriptors for Object and Scene Recognition , 2010, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[26]  Steven J. Gortler,et al.  A perception-based color space for illumination-invariant image processing , 2008, ACM Trans. Graph..

[27]  B. N. Chatterji,et al.  An FFT-based technique for translation, rotation, and scale-invariant image registration , 1996, IEEE Trans. Image Process..

[28]  Arnold W. M. Smeulders,et al.  Color Based Object Recognition , 1997, ICIAP.

[29]  Michael J. Swain,et al.  Color indexing , 1991, International Journal of Computer Vision.

[30]  P. Bekaert,et al.  SIFT-CCH: Increasing the SIFT distinctness by Color Co-occurrence Histograms , 2007, 2007 5th International Symposium on Image and Signal Processing and Analysis.

[31]  T. K. Leungfj,et al.  Finding Faces in Cluttered Scenes using Random Labeled Graph Matching , 1995 .

[32]  Min-Seok Choi,et al.  A novel two stage template matching method for rotation and illumination invariance , 2002, Pattern Recognit..

[33]  Yi-Hsien Lin,et al.  Template matching using the parametric template vector with translation, rotation and scale invariance , 2008, Pattern Recognit..

[34]  Shun'ichi Kaneko,et al.  Using orientation codes for rotation-invariant template matching , 2004, Pattern Recognit..

[35]  Boguslaw Cyganek,et al.  Circular road signs recognition with soft classifiers , 2007, Integr. Comput. Aided Eng..

[36]  Vincent Lemaire,et al.  Illumination-Invariant Color Image Correction , 2006, IWICPAS.

[37]  Koen E. A. van de Sande,et al.  Evaluation of color descriptors for object and scene recognition , 2008, 2008 IEEE Conference on Computer Vision and Pattern Recognition.

[38]  Brian V. Funt,et al.  Color Constant Color Indexing , 1995, IEEE Trans. Pattern Anal. Mach. Intell..

[39]  Matthijs C. Dorst.  Distinctive Image Features from Scale-Invariant Keypoints , 2011 .