Supervised and unsupervised pattern recognition: feature extraction and computational intelligence
Supervised and unsupervised pattern recognition: feature extraction and computational intelligence
R-Histogram: quantitative representation of spatial relations for similarity-based image retrieval
MULTIMEDIA '03 Proceedings of the eleventh ACM international conference on Multimedia
Attention-driven image interpretation with application to image retrieval
Pattern Recognition
Moments and Moment Invariants in Pattern Recognition
Moments and Moment Invariants in Pattern Recognition
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In this paper, a novel feature for shape-based image classification is proposed, in which a set of randomly dilating discs are distributed on an unknown regular or irregular shape, and the radius histogram of discs is used to represent the target shape. By such doing, a shape can be modeled by the radius histogram. The proposed feature is rather effective for shape retrieval with rotation and scaling invariance. The proposed feature is particularly effective in the retrieval of string-linked objects in which conventional approaches may fail badly. Experimental results on seven shapes and string-linked objects show that our proposed new feature is very effective in shape classification and shape-based image retrieval.