TY  - JOUR
T1  - Feature Extraction and Selection for Image Retrieval
AU - , J.P. Ananth AU - , M.A. Leo Vijilous AU - , V. Subbiah Bharathi 
JO  - International Journal of Soft Computing
VL  - 3
IS  - 2
SP  - 84
EP  - 87
PY  - 2008
DA  - 2001/08/19
SN  - 1816-9503
DO  - ijscomp.2008.84.87
UR  - https://makhillpublications.co/view-article.php?doi=ijscomp.2008.84.87
KW  - Feature extraction
KW  -feature selection
KW  -content-based image retrieval
KW  -principle component analysis
KW  -discriminant analysis
AB  - In this study feature extraction process is analyzed and a new set of edge features is proposed. A revised edge-based structural feature extraction approach is introduced. A principle  feature selection algorithm is also proposed for new feature analysis and feature selection. The results of the PFA is tested and compared to the original feature set, random selections, as well as those from Principle Component Analysis and multivariate linear discriminant analysis. The experiments showed that the proposed features perform better than wavelet moment for image retrieval in a real world image database and the feature selected by the proposed algorithm yields comparable results to original feature setstudy better results than random sets.
ER  -