Image recognition system based on novel measures of image similarity and cluster validity

被引：5
|
作者：
Yen, Chia-Yu [2 ,3 ]
Cios, Krzysztof J. [1 ,2 ,4 ,5 ]
机构：
[1] Virginia Commonwealth Univ, Dept Comp Sci, Richmond, VA 23284 USA
[2] Univ Colorado, Dept Comp Sci & Engn, Denver, CO 80217 USA
[3] Univ Colorado, Dept Chem & Biochem, Boulder, CO 80309 USA
[4] Univ Colorado, Dept Comp Sci, Boulder, CO 80309 USA
[5] Polish Acad Sci, PL-00901 Warsaw, Poland
来源：
NEUROCOMPUTING | 2008年 / 72卷 / 1-3期
关键词：
Image recognition; Image similarity measures; Cluster validity;
D O I：
10.1016/j.neucom.2007.12.018
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
We introduce an image recognition system that does not require availability of a complete training data. The system consists of a constrained K-Means clustering algorithm and an image recognition neural network. For finding similarity between images we use a novel image similarity measure and introduce a new image cluster validity measure to determine the most probable number of clusters. Extensive testing on several image datasets indicates good performance of the system. (C) 2008 Elsevier B.V. All rights reserved.
引用
收藏
页码：401 / 412
页数：12
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