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