Title :
Image Retrieval Based on the Local Multi-features Statistical Method
Author :
Liu, Liu ; Jin, Hui-ming ; Li, Jian-Xun
Author_Institution :
Sch. of Electron., Inf. & Electr. Eng., Shanghai Jiao tong Univ. Shanghai, Shanghai, China
Abstract :
The spatial geometrical features of the objects are widely used in the image matching and retrieval. The popular algorithms of the spatial feature detection are designed for gray images, which failed to make use of the color information in color images. However, the color information is absolutely nontrivial in discrimination of different objects, vacancy of which would lead to miss judgment. Based on the illumination model, a matching algorithm using the combined color and spatial features is proposed to extract the local invariant features of the objects in this paper. The robust of our algorithm is strengthened and the time-consuming in matching is reduced compared to SIFT algorithm.
Keywords :
feature extraction; image colour analysis; image matching; image retrieval; object detection; statistics; color feature; color image; color information; gray image; illumination model; image matching; image retrieval; local invariant feature extraction; local multifeature statistical method; matching algorithm; spatial feature detection; spatial geometrical feature; Color; Feature extraction; Image color analysis; Image edge detection; Lighting; Reflection; Robustness; image matching; image retrieval; local feature; shadow-shading invariant;
Conference_Titel :
Communication Systems and Network Technologies (CSNT), 2012 International Conference on
Conference_Location :
Rajkot
Print_ISBN :
978-1-4673-1538-8
DOI :
10.1109/CSNT.2012.61
