Abstract
The Distance Transform is a powerful tool that has been used in many computer vision tasks. In this paper, the use of relevant maxima in distance transform’s medial axis is proposed as a method for fast image data reduction. These disc-shaped maxima include morphological information from the object they belong to, and because maxima are located inside homogeneous regions, they also sum up chromatic information from the pixels they represent. Thus, maxima can be used instead of single pixels in algorithms which compute relations among pixels, effectively reducing computation times. As an example, a fast method for color image segmentation is proposed, which can also be used for textured zones detection. Comparisons with mean shift segmentation algorithm are shown.
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References
Arlandis, J., Perez-Cortes, J.C.: The continuos distance transformation: a generalization of distance transformation for continous-valued images. In: Proceedings of the VIII SNRFAI, Spain, vol. 1, pp. 195–202 (1999)
Gooch, A.A., Olsen, S.C., Tumblin, J., Gooch, B.: Color2Gray: Salience-Preserving Color Removal. ACM Transactions on Graphics (Proceedings of ACM SIGGRAPH ) 24(3), 634–639 (2005)
Antón-Canalís, L., Hernández-Tejera, M., Sánchez-Nielsen, E.: AddCanny: Edge Detector for Video Processing. In: Blanc-Talon, J., Philips, W., Popescu, D., Scheunders, P. (eds.) ACIVS 2006. LNCS, vol. 4179, pp. 501–512. Springer, Heidelberg (2006)
Borgefors, G.: Hierarchical chamfer matching: A parametric edge matching algorithm. IEEE Transactions on Pattern Analysis and Machine Intelligence 10(6), 849–865 (1988)
Cho, G.S., Ryeun, J.: Mobile robot path planning by circular scan code and circular distance transform method. In: Proc. of International Conference on Intelligent Computing (ICIC), pp. 1102–1107 (2006)
Comaniciu, D., Meer, P.: Mean shift: A robust approach toward feature space analysis. IEEE Trans. Pattern Anal. Machine Intell. 24, 603–619 (2002)
Fernández-Vidal, S., Bardinet, E., Malandain, G., Damas, S., De la Blanca Capilla, N.P.: Object Representation and Comparison Inferred from Its Medial Axis. In: International Conference on Pattern Recognition (ICPR 2000), Barcelone, Espagne, vol. 1, pp. 1712–1715 (2000)
Borgefors, G.: Distance Transformations in Digital Images. Computer Vision, Graphics and Image Processing 34, 344–371 (1986)
Huttenlocher, D., Klanderman, G., Rucklidge, W.: Comparing images using the hausdorff distance. IEEE Transactions on Pattern Analysis and Machine Intelligence 15(9), 850–863 (1993)
Intel’s Open Source Computer Vision Library, http://www.intel.com/technology/computing/opencv
Canny, J.: A Computational approach to Edge Detection. IEEE Transactions on Pattern Analysis and Machine Intelligence 8(6) (1986)
Paglieroni, D.W.: Distance Transforms. Computer Vision, Graphics and Image Processing: Graphical Models and Image Processing 54, 56–74 (1992)
Pietikäinen, M.: Image analysis with local binary patterns. In: Kalviainen, H., Parkkinen, J., Kaarna, A. (eds.) SCIA 2005. LNCS, vol. 3540, pp. 115–118. Springer, Heidelberg (2005)
Strzodka, R., Telea, A.: Generalized Distance Transforms and skeletons in graphics hardware. In: Proceedings of EG/IEEE TCVG Symposium on Visualization (VisSym ’04), pp. 221–230 (2004)
Roerdink, J.B.T.M., Meijster, A.: The Watershed Transform: Definitions, Algorithms and Parallelization Strategies. Fundamenta Informatica 41, 187–228 (2000)
Rosin, P.L., West, G.A.W.: Salience distance transforms. CVGIP: Graphical Models and Image Processing 57(6), 483–521 (1995)
Shih, F.Y., Wu, Y.-T.: The efficient algorithms for achieving Euclidean distance transformation. IEEE Transactions on Image Processing 13(8), 1078–1091 (2004)
Weeks, A.R., Hague, G.E.: Color segmentation in the HSI color space using the K-means algorithm. In: Proc. of Conference on Nonlinear Image Processing, vol. VIII, pp. 143–154 (1997)
Yang, R., Mirmehdi, M., Xie, X.: A Charged Active Contour Based on Electrostatics. In: Blanc-Talon, J., Philips, W., Popescu, D., Scheunders, P. (eds.) ACIVS 2006. LNCS, vol. 4179, pp. 173–184. Springer, Heidelberg (2006)
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Antón-Canalís, L., Hernández-Tejera, M., Sánchez-Nielsen, E. (2007). Analysis of Relevant Maxima in Distance Transform. An Application to Fast Coarse Image Segmentation. In: Martí, J., Benedí, J.M., Mendonça, A.M., Serrat, J. (eds) Pattern Recognition and Image Analysis. IbPRIA 2007. Lecture Notes in Computer Science, vol 4477. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-72847-4_14
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DOI: https://doi.org/10.1007/978-3-540-72847-4_14
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