Automatic interpretation based on robust segmentation and shape-extraction

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 1614, Issue , 1999, Pages 769-776

  Frederix, Greet ^a   Pauwels, Eric J ^a,b  

^a UNIVERSITY OF LEUVEN   (Belgium)

^b Fund for Scientific Research FWO   (Belgium)

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL INTELLIGENCE; COMPUTERS;

AUTOMATIC ANNOTATION; NON-PARAMETRIC; REAL IMAGES; ROBUST SEGMENTATION; SALIENT REGIONS; SHAPE EXTRACTION;

INFORMATION SYSTEMS;

EID: 79957480366     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: None     Document Type: Conference Paper

References (7)

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3. Leonard Kaufman and Peter J. Rousseeuw: Finding Groups in Data: An Introduction to Cluster Analysis. J. Wiley and Sons, 1990. 770.
4. L. J. Latecki and R. Lakämper: Convexity Rule for Shape Decomposition Based on Discrete Contour Evolution. To appear in Int. J. of Computer Vision and Image Understanding. 772.
5. E. J. Pauwels and G. Frederix: Non-parametric Clustering for Segmentation and Grouping. Proc. VLBV'98, Beckman Institute, Urbana-Champaign, Oct. 1998, pp. 133-136. 771.
6. J. Shi and J. Malik: Normalized Cuts and Image Segmentation. Proc. IEEE Conf. oon Comp. Vision and Pattern Recognition, San Juan, Puerto Rico, June 1997.
7. K. Siddiqi and B. Kimia: Parts of Visual Form: Computational Aspects. IEEE Trans. PAMI, Vol. 17, No. 3, March 1995. 772, 773.