DocumentCode
1733358
Title
A new algorithm to feature detection
Author
Xu, Xingwei ; Wang, Haiying
Author_Institution
Beijing Key Lab. of Network Syst. & Network Culture, Beijing Univ. of Posts & Telecommun., Beijing, China
Volume
2
fYear
2011
Firstpage
699
Lastpage
703
Abstract
This paper describes a new feature detection algorithm, which bases on color and curvature. Since color provides valuable information in object recognition and description, a color invariant space is adopted instead of the gray space. With this method, the distinctive features extracted from images are invariant to image scale and rotation. To reduce the computational complexity and improve the quality of detection, the cascade filtering approach is employed. Details of the new feature descriptor are described, along with test results.
Keywords
computational complexity; image colour analysis; object detection; cascade filtering; color invariant space; computational complexity; curvature; feature detection; gray space; image scale; object recognition; Detection algorithms; Feature extraction; Filtering; Image color analysis; Noise; Object recognition; Shape; color; curvature; descriptor; feature detection;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer Science and Network Technology (ICCSNT), 2011 International Conference on
Conference_Location
Harbin
Print_ISBN
978-1-4577-1586-0
Type
conf
DOI
10.1109/ICCSNT.2011.6182062
Filename
6182062
Link To Document