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Adaptive Image Segmentation by Combining Photometric Invariant Region and Edge Information
June 2002 (vol. 24 no. 6)
pp. 848-852

An adaptive image segmentation scheme is proposed employing the Delaunay triangulation for image splitting. The tessellation grid of the Delaunay triangulation is adapted to the semantics of the image data by combining region and edge information. To achieve robustness against imaging conditions (e.g., shading, shadows, illumination, and highlights), photometric invariant similarity measures, and edge computation is proposed. Experimental results on synthetic and real images show that the segmentation method is robust to edge orientation, partially weak object boundaries, and noisy, but homogeneous regions. Furthermore, the method is robust to a large degree to varying imaging conditions.

[1] L. Wolff, S.A. Shafer, and G.E. Healey, Physics-Based Vision: Principles and Practice. Jones and Bartlett, 1992.
[2] G. Klinker, S. Shafer, and T. Kanade, “A Physical Approach to Color Image Understanding,” Int'l J. Computer Vision, vol. 4, pp. 7-38, 1990.
[3] S.A. Shafer, “Using Color to Separate Reflection Components,” Color Resolution Applications, vol. 10, no. 4, pp. 210-218, 1985.
[4] R. Bajcsy, S.W. Lee, and A. Leonardis, “Detection of Diffuse and Specular Interface Reflections and Inter-Reflections by Color Image Segmentation,” Int'l J. Computer Vision, vol. 17, pp. 241-272, 1996.
[5] G. Healey,“Segmenting images using normalized color,” IEEE Trans. Systems, Man, and Cybernetics, vol. 22, pp. 64-73, Jan. 1992.
[6] M. Tabb and N. Ahuja, “Multiscale Image Segmentation by Integrated Edge and Region Detection,” IEEE Trans. Image Processing, vol. 6, no. 5, pp. 642-655, 1997.
[7] A. Chakraborty and J.S. Duncan, Game-Theoretic Integration for Image Segmentation IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 21, no. 1, pp. 12-30, Jan. 1999.
[8] A. Wu, “Adaptive Split-and-Merge Segmentation Based on Piecewise Least-Square Approximation,” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 15, no. 8, Aug. 1993.
[9] D.L. Lee and B.J. Schachter, “Two Algorithms for Constructing a Delaunay Triangulation,” Int'l J. Computer and Information Science, vol. 9, no. 3, pp. 219-424, 1980.
[10] F. Davoine, M. Antonini, J.M. Chassery, and M. Barlaud, “Fractal Image Compression Based on Delaunay Triangulation and Vector Quantization,” IEEE Trans. Image Processing, vol. 5, no. 2, pp. 338-346, 1996.
[11] M. Tüceryan and A.K. Jain,“Texture segmentation using Voronoi polygons,” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 12, no. 2, pp. 211-216, Feb. 1990.
[12] P.J. Besl and R.C. Jain,“Segmentation through variable-order surface fitting,” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 10, no. 2, pp. 167-191, Mar. 1988.
[13] B.M. ter Haar Romeny,L.M.J. Florack,J.J. Koenderink,, and M.A. Viergever,“Scale-space: its natural operators and differential invariants,” Int’l Conf. Information Processing in Medical Imaging, vol. 511, Lecture Notes in Computer Sciences, pp. 239-255,Springer-Verlag, 1992.
[14] B. Funt and G. Finlayson, "Color Constant Color Indexing," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 17, no. 5, pp. 522-529, May 1995.
[15] T. Gevers and A.W.M. Smeulders, “Color Based Object Recognition,” Pattern Recognition, no. 32, pp. 453-464, 1999.
[16] S.K. Nayar and R.M. Bolle, "Reflectance based object recognition," Int'l J. Computer Vision, in press.
[17] T. Gevers, “Robust Histogram Construction from Color Invariants,” Proc. Int'l Conf. Computer Vision, vol. I, pp. 615-620, July 2001.
[18] S. Di Zenzo, “A Note on the Gradient of a Multi-Image,” Computer Vision, Graphics, and Image Processing, vol. 33, no. 1, pp. 116-125, Jan. 1986.
[19] G. Sapiro and D. Ringach, “Anisotropic Diffusion of Multivalued Images with Applications to Color Filtering,” IEEE Trans. Image Processing, vol. 5, pp. 1582-1586, 1996.
[20] Y.J. Zhang and J.J. Gerbrands, “Comparison of Thresholding Techniques Using Synthetic Images and Ultimate Measurement Accuracy,” Proc. IAPR, Int'l Conf. Pattern Recogniation (ICPR), vol. B, pp. 209-213, 1992.

Index Terms:
Image segmentation, adaptive splitting, integrating region and edge information, photometric color invariance, noise robustness.
Citation:
Theo Gevers, "Adaptive Image Segmentation by Combining Photometric Invariant Region and Edge Information," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 24, no. 6, pp. 848-852, June 2002, doi:10.1109/TPAMI.2002.1008391
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