The Community for Technology Leaders
RSS Icon
Subscribe
Issue No.09 - Sept. (2012 vol.34)
pp: 1827-1841
Yu Sun , Dept. of Electr. Eng., Univ. of California, Riverside, CA, USA
Bir Bhanu , Center for Res. in Intell. Syst., Univ. of California, Riverside, CA, USA
ABSTRACT
This paper presents a new symmetry-integrated region-based image segmentation method. The method is developed to obtain improved image segmentation by exploiting image symmetry. It is realized by constructing a symmetry token that can be flexibly embedded into segmentation cues. Interesting points are initially extracted from an image by the SIFT operator and they are further refined for detecting the global bilateral symmetry. A symmetry affinity matrix is then computed using the symmetry axis and it is used explicitly as a constraint in a region growing algorithm in order to refine the symmetry of the segmented regions. A multi-objective genetic search finds the segmentation result with the highest performance for both segmentation and symmetry, which is close to the global optimum. The method has been investigated experimentally in challenging natural images and images containing man-made objects. It is shown that the proposed method outperforms current segmentation methods both with and without exploiting symmetry. A thorough experimental analysis indicates that symmetry plays an important role as a segmentation cue, in conjunction with other attributes like color and texture.
INDEX TERMS
matrix algebra, computational geometry, feature extraction, image segmentation, segmentation cue, reflection symmetry, symmetry-integrated region-based image segmentation, image symmetry, SIFT operator, global bilateral symmetry, symmetry affinity matrix, symmetry axis, region growing algorithm, multiobjective genetic search, Image segmentation, Segmentation algorithms, comparison of segmentation algorithms., Local and global symmetry, region growing, symmetry affinity, segmentation and symmetry evaluation
CITATION
Yu Sun, Bir Bhanu, "Reflection Symmetry-Integrated Image Segmentation", IEEE Transactions on Pattern Analysis & Machine Intelligence, vol.34, no. 9, pp. 1827-1841, Sept. 2012, doi:10.1109/TPAMI.2011.259
REFERENCES
[1] J.S. Stahl and S. Wang, "Global Optimal Grouping for Symmetric Closed Boundaries by Combining Boundary and Region Information," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 30, no. 3, pp. 395-411, Mar. 2008.
[2] D. Raviv, A.M. Bronstein, M.M. Bronstein, and R. Kimmel, "Full and Partial Symmetries of Non-Rigid Shapes," Int'l J. Computer Vision, vol. 89, no. 1, pp. 18-39, Aug. 2010.
[3] J.S. Stahl and S. Wang, "Globally Optimal Grouping for Symmetric Boundaries," Proc. IEEE CS Conf. Computer Vision and Pattern Recognition, 2006.
[4] D. Shen, K.T. Cheung, and E.K. Teoh, "Symmetry Detection by Generalized Complex (GC) Moments: A Closed-Form Solution," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 21, no. 5, pp. 466-476, May 1999.
[5] D. Raviv, A.M. Bronstein, M.M. Bronstein, and R. Kimmel, "Symmetries of Non-Rigid Shapes," Proc. 11th IEEE Int'l Conf. Computer Vision, 2007.
[6] P.J. Giblin and B. Kimia, "On the Intrinsic Reconstruction of Shape from Its Symmetries," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 25, no. 7, pp. 895-911, July 2003.
[7] G. Marola, "A Technique for Finding the Symmetry Axis of Implicit Polynomial Curves under Perspective Projection," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 27, no. 3, pp. 465-470, Mar. 2005.
[8] A.V. Tuzikov, O. Colliot, and I. Bloch, "Evaluation of the Symmetry Plane in 3D MR Brain Images," Pattern Recognition Letters, vol. 24, no. 14, pp. 2219-2233, Oct. 2003.
[9] B. Combes, R. Hennessy, J. Waddington, N. Roberts, and S. Prima, "Automatic Symmetry Plane Estimation of Bilateral Objects in Points Clouds," Proc. IEEE Conf. Computer Vision and Pattern Recognition, 2008.
[10] V.S.N. Prasad and B. Yegnanarayana, "Finding Axes of Symmetry from Potential Fields," IEEE Trans. Image Processing, vol. 13, no. 12, pp. 1559-1566, Dec. 2004.
[11] P. Cicconi and M. Kunt, "Symmetry-Based Image Segmentation," Proc. SPIE, vol. 1977, no. 378, pp. 378-384, Oct. 1993.
[12] T. Liu, D. Geiger, and A.L. Yuille, "Segmenting by Seeking the Symmetry Axis," Proc. Int'l Conf. Pattern Recognition, 1998.
[13] R. Shor and N. Kiryati, "Towards Segmentation from Multiple Cues: Symmetry and Color," Proc. Int'l Workshop Theoretical Foundations of Computer Vision: Multi-Image Analysis, 2000.
[14] A. Gupta, V.S.N. Prasad, and L.S. Davis, "Extracting Regions of Symmetry," Proc. Int'l Conf. Image Processing, 2005.
[15] T. Riklin-Raviv, N. Kiryati, and N. Sochen, "Segmentation by Level Sets and Symmetry," Proc. IEEE CS Conf. computer Vision and Pattern Recognition, 2006.
[16] F. Jiao, D. Fu, and S. Bi, "Brain Image Segmentation Based on Bilateral Symmetry Information," Proc. Second Int'l Conf. Bioinformatics and Biomedical Eng., 2008.
[17] S. Saha and S. Bandyopadhyay, "MRI Brain Image Segmentation by Fuzzy Symmetry Based Genetic Clustering Technique," Proc. IEEE Congress on Evolutionary Computation, 2007.
[18] F.P.G. Bergo, A.X. Falcao, C.L. Yasuda, and F. Cendes, "FCD Segmentation Using Texture Asymmetry of MR-T1 Images of the Brain," Proc. IEEE Int'l Symp. Biomedical Imaging, 2008.
[19] N. Ray, R. Greiner, and A. Murtha, "Using Symmetry to Detect Abnormalities in Brain MRI," CS of India Comm., vol. 31, no. 19, pp. 7-10, 2008.
[20] Y. Liu, K.L. Schmidt, J.F. Cohn, and S. Mitra, "Facial Asymmetry Quantification for Expression Invariant Human Identification," Computer Vision and Image Understanding, vol. 91, nos. 1-2,special issue on face recognition, pp. 138-159, July-Aug., 2003.
[21] E. Saber and A. Tekalp, "Frontal-View Face Detection and Facial Feature Extraction Using Color, Shape and Symmetry Based Cost Functions," Pattern Recognition Letters, vol. 19, no. 8, pp. 669-680, June 1998.
[22] Q.B. Sun, W.M. Huang, and J.K. Wu, "Face Detection Based on Color and Local Symmetry Information," Proc. IEEE Int'l Conf. Automatic Face and Gesture Recognition, 1998.
[23] J.G. Wang and E. Sung, "Frontal-View Face Detection and Facial Feature Extraction Using Color and Morphological Operations," Pattern Recognition Letters, vol. 20, no. 10, pp. 1053-1068, Oct. 1999.
[24] W.H. Li and L. Kleeman, "Real Time Object Tracking Using Reflectional Symmetry and Motion," Proc. IEEE Int'l Conf. Intelligent Robots and Systems, 2006.
[25] W.H. Li, A. Zhang, and L. Kleeman, "Fast Global Reflectional Symmetry Detection for Robotic Grasping and Visual Tracking," Proc. Australasian Conf. Robotics and Automation, 2005.
[26] S. Thrun and B. Wegbreit, "Shape from Symmetry," Proc. 10th IEEE Int'l Conf. Computer Vision, 2005.
[27] M. Park, S. Lee, P. Chen, S. Kashyap, A.A. Butt, and Y. Liu, "Performance Evaluation of State-of-the-Art Discrete Symmetry Detection Algorithms," Proc. IEEE Conf. Vision and Pattern Recognition, 2008.
[28] H. Zabrodsky, S. Peleg, and D. Avnir,"Symmetry as a Continuous Feature," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 17, no. 12, pp. 1154-1166, Dec. 1995.
[29] G. Loy and J. Eklundh, "Detecting Symmetry and Symmetric Constellations of Features," Proc. European Conf. Computer Vision, 2006.
[30] D.G. Lowe, "Distinctive Image Features from Scale-Invariant Keypoints," Int'l J. Computer Vision, vol. 60, no. 2, pp. 91-110, Nov. 2004.
[31] S.P. Kodali, R. Kudikala, and K. Deb, "Multi-Objective Optimization of Surface Grinding Process Using NSGA-II," Proc. First Int'l Conf. Emerging Trends in Eng. and Technology, pp. 763-767, 2008.
[32] C. Xu and J.L. Prince, "Snakes, Shapes, and Gradient Vector Flow," IEEE Trans. Image Processing, vol. 7, no. 3, pp. 359-369, Mar. 1998.
[33] Y. Sun, B. Bhanu, and S. Bhanu, "Automatic Symmetry-Integrated Brain Injury Detection in MRI Sequences," Proc. IEEE CS Conf. Computer Vision and Pattern Recognition Workshop, 2009.
[34] R. Adams and L. Bischoff, "Seeded Region Growing," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 16, no. 6, pp. 641-647, June 1994.
[35] D. Comaniciu and P. Meer, "Mean Shift: A Robust Approach Toward Feature Space Analysis," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 24, no. 5, pp. 603-619, May 2002.
[36] S. Beucher, "The Watershed Transformation Applied to Image Segmentation," Proc. Conf. Signal and Image Processing in Microscopy and Microanalysis, 1991.
[37] A.R. Smith, "Color Gamut Transform Pairs," ACM Computer Graphics, Proc. Siggraph, vol. 12, no. 3, pp. 12-19, Aug. 1978.
[38] M. Borsotti, P. Campadelli, and R. Schettini, "Quantitative Evaluation of Color Image Segmentation Results," Pattern Recognition Letters, vol. 19, no. 8, pp. 741-747, June 1998.
[39] J. Shi and J. Malik, "Normalized Cuts and Image Segmentation," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 22, no. 8, pp. 888-905, Aug. 2000.
[40] Y. Sun and B. Bhanu, "Symmetry Integrated Region Based Image Segmentation," Proc. IEEE Conf. Computer Vision and Pattern Recognition, 2009.
[41] A. Hafiane, S. Chabrier, C. Rosenberger, and H. Laurent, "A New Supervised Evaluation Criterion for Region Based Segmentation Methods," Proc. Ninth Int'l Conf. Advanced Concepts for Intelligent Vision Systems, 2007.
[42] L. Fei-Fei, R. Fergus, and P. Perona, "One-Shot Learning of Object Categories," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 28, no. 4, pp. 594-611, Apr. 2006.
[43] X. Ren, C. Fowlkes, and J. Malik, "Figure/Ground Assignment in Natural Images," Proc. European Conf. Computer Vision, 2006.
[44] M. Pauly, N.J. Mitra, J. Wallner, H. Pottmann, and L. Guibas, "Discovering Structural Regularity in 3D Geometry," Proc. ACM Siggraph, 2008.
[45] N.J. Mitra, A. Bronstein, and M. Bronstein, "Intrinsic Regularity Detection in 3D Geometry," Proc. 11th European Conf. Computer Vision, 2010.
[46] N.J. Mitra, L. Guibas, and M. Pauly, "Symmetrization," Proc. ACM Siggraph, 2007.
[47] M. Ovsjanikov, J. Sun, and L. Guibas, "Global Intrinsic Symmetries of Shapes," Computer Graphics Forum, vol. 27, no. 5, pp. 1341-1348, July 2008.
[48] O. Teboul, L. Simon, P. Koutsourakis, and N. Paragios, "Segmentation of Building Facades Using Procedural Shape Priors," Proc. IEEE Conf. Computer Vision and Pattern Recognition, 2010.
[49] M. Cho and K. Mu Lee, "Bilateral Symmetry Detection and Segmentation via Symmetry-Growing," Proc. British Machine Vision Conf., 2009.
[50] J. Liu and Y. Liu, "Curved Reflection Symmetry Detection with Self-Validation," Proc. Asian Conf. Computer Vision, 2010.
[51] Y. Liu, H. Hel-Or, C.S. Kaplan, and L.V. Gool, "Computational Symmetry in Computer Vision and Computer Graphics," Foundations and Trends in Computer Graphics and Vision, vol. 5, nos. 1/2, pp. 1-195, 2010.
[52] Supplemental Material for This Paper, http://doi.ieeecomputer society.org/10.1109 TPAMI.2011.259, 2012.
[53] S. Lee and Y. Liu, "Skewed Rotation Symmetry Group Detection," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 32, no. 9, pp. 1659-1672, Sept. 2010.
[54] S. Lee and Y. Liu, "Curved Glide-Reflection Symmetry Detection," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 34, no. 2, pp. 266-278, Feb. 2012.
[55] Q. Guo, F. Guo, and J. Shao, "Irregular Shape Symmetry Analysis: Theory and Application to Quantitative Galaxy Classification," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 32, no. 10, pp. 1730-1743, Oct. 2010.
[56] A. Hooda, M. Bronstein, A. Bronstein, and R.P. Horaud, "Shape Palindromes: Analysis of Intrinsic Symmetries in 2D Articulated Shapes," Proc. Int'l Conf. Scale Space and Variational Methods in Computer Vision, 2011.
[57] A.M. Bruckstein and D. Shaked, "Skew Symmetry Detection via Invariant Signatures," Pattern Recognition, vol. 31, no. 2, pp. 181-192, Feb. 1998.
[58] J. Hays, M. Leordeanu, A.A. Efros, and Y. Liu, "Discovering Texture Regularity as a Higher-Order Correspondence Problem," Proc. European Conf. Compuetr Vision, 2006.
[59] M. Park, K. Brocklehurst, R. Collins, and Y. Liu, "Deformed Lattice Detection in Real-World Images using Mean-Shift Belief Propagation," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 31, no. 10, pp. 1804-1816, Oct. 2009.
[60] Y. Ran, Q. Zheng, R. Chellappa, and T.M. Strat, "Applications of a Simple Characterization of Human Gait in Surveillance," IEEE Trans. Systems, Man, and Cybernetics, vol. 40, no. 4, pp. 1009-1020, Aug. 2010.
[61] S. Lee, Y. Liu, and R. Collins, "Shape Variation-Based Frieze Pattern for Robust Gait Recognition," Proc. IEEE Conf. Computer Vision and Pattern Recognition, 2007.
27 ms
(Ver 2.0)

Marketing Automation Platform Marketing Automation Tool