DocumentCode :
556712
Title :
Automatic unsupervised shape recognition technique using moment invariants
Author :
Barbu, Tudor
Author_Institution :
Iasi Branch, Inst. of Comput. Sci., Iasi, Romania
fYear :
2011
fDate :
14-16 Oct. 2011
Firstpage :
1
Lastpage :
4
Abstract :
We approach the shape recognition domain in this paper. After an introduction in the image shape analysis domain, we describe a shape feature extraction technique using moment-based measures which are invariant to geometric transforms. Then, an automatic unsupervised feature vector classification approach is proposed. It is based on a sequence of hierarchical agglomerative region-growing clustering algorithms and a measure based on cluster validation indexes. The results of this provided recognition technique can be applied successfully in important domains, such as object recognition, shape-based image content indexing and retrieval.
Keywords :
feature extraction; method of moments; pattern classification; shape recognition; transforms; automatic unsupervised feature vector classification approach; automatic unsupervised shape recognition technique; cluster validation indexes; geometric transforms; hierarchical agglomerative region-growing clustering algorithms; image shape analysis domain; moment invariants; moment-based measures; shape feature extraction technique; shape recognition domain; Clustering algorithms; Feature extraction; Image recognition; Indexes; Object recognition; Shape; Support vector machine classification;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
System Theory, Control, and Computing (ICSTCC), 2011 15th International Conference on
Conference_Location :
Sinaia
Print_ISBN :
978-1-4577-1173-2
Type :
conf
Filename :
6085654
Link To Document :
بازگشت