Title :
A new algorithm of image retrieval based on multiple-feature and FSIM
Author :
Ziping Ma ; Baosheng Kang
Author_Institution :
Inst. of Inf. Sci. & Technol., Northwest Univ., Xi´an, China
Abstract :
In order to reduce the computation cost of extracting feature, a new algorithm for image retrieval is proposed. This method utilize multiple-feature including ellipse measuring as shape feature, phase congruent and gradient magnitude as the contrast feature for image retrieval in this paper. It not only can fill up a deficiency of the contrast invariant of phase congruent, but also can fully utilize scale and rotation invariance of ellipse measuring. To evaluate the effectiveness of the proposed method, we carried out a series of experiments on shape216 and three color image databases. The experiments show that the proposed method in this paper is more efficient than conventional algorithms.
Keywords :
feature extraction; image retrieval; FSIM; color image databases; contrast feature; contrast invariance; ellipse measuring feature; feature extraction; frequency structural similarity; gradient magnitude feature; image retrieval; multiple-feature; phase congruent feature; rotation invariance; scale invariance; shape feature; shape216 image databases; Ellipse measure; FSIM; Gradient magnitude; Image Retrieval; Phase congruent;
Conference_Titel :
Computer Science and Network Technology (ICCSNT), 2012 2nd International Conference on
Conference_Location :
Changchun
Print_ISBN :
978-1-4673-2963-7
DOI :
10.1109/ICCSNT.2012.6526230