DocumentCode :
2440512
Title :
Enhanced visual evaluation of feature extractors for image mining
Author :
Rodrigues, J.F. ; Traina, Agma J M ; Traina, Caetano, Jr.
Author_Institution :
Comput. Sci. Dept., Sao Paulo Univ., Sao Carlos, Brazil
fYear :
2005
fDate :
2005
Firstpage :
45
Abstract :
Summary form only given. This paper introduces a novel approach to evaluate, timely and effectively, the suitability of new image feature extraction techniques concerning similarity queries using CBIR systems. The proposed approach is based on two measurements derived from spatial properties intuitively and naturally perceived in spatial domains, and that can also be verified in multidimensional spaces. To bear out our proposal, we show that the insights obtained by the proposed measurements comply with the well-known analysis methods based on the precision and recall approach.
Keywords :
content-based retrieval; data mining; feature extraction; image retrieval; CBIR systems; enhanced visual evaluation; image feature extraction; image mining; multidimensional spaces; similarity queries; Computer science; Data mining; Feature extraction; Humans; Image databases; Image generation; Image processing; Image retrieval; Multidimensional systems; Proposals;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Systems and Applications, 2005. The 3rd ACS/IEEE International Conference on
Print_ISBN :
0-7803-8735-X
Type :
conf
DOI :
10.1109/AICCSA.2005.1387042
Filename :
1387042
Link To Document :
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