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By Obinata G., Dutta A. (eds.)

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Over-segmentation, or multiple detections of a single surface, results in an incorrect topology. Under-segmentation, or insufficient separation of multiple surfaces, results in a subset of the correct topology and a deformed geometry. A missed classification is used when a segmenter fails to find a surface which appears in the image (false negative). A noise classification is used when the segmenter supposes the existence of a surface which is not in the image (false positive). Obviously, these metrics could have varying importance in different applications.

2004). A Snake Model for Object Tracking in Natural Sequences, Signal Process Image Comm, Vol. 19, No. 3, March 2004, pp. 219-238, ISSN: 0923-5965 Venkatesh, S. & Owens, R. (1990). On the Classification of Image Features, Pattern Recognition Letters, Vol. 11, No. 5, May 1990, pp. A. H. (1994). Representing Moving Images with Layers, IEEE Trans Pattern Anal Mach Intell, Vol. 3, No. 5, September 1994, pp. B. J. (1985). Model for Human Visual-Motion Sensing, J Opt Soc Am A, Vol. 2, No. 2, February 1985, pp.

Forsyth D. , 2003. , Image segmentation by unifying region and boundary information, IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 12, pp. 929-948, 1990. , Singapore, 1992. , Range image segmentation by curve grouping, In K. Dobrovodský, editor, Proceedings of the 7th International Workshop on Robotics in Alpe-Adria-Danube Region, pages 339--344, Bratislava, June 1998. ASCO Art. Haralick R. , Shapiro L. , Survey: Image segmentation techniques, Computer Vision, Graphics, and Image Processing, vol.

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Vision systems: segmentation and pattern recognition by Obinata G., Dutta A. (eds.)

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