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
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;
Conference_Titel :
Computer Science and Network Technology (ICCSNT), 2011 International Conference on
Conference_Location :
Harbin
Print_ISBN :
978-1-4577-1586-0
DOI :
10.1109/ICCSNT.2011.6182062
