Paper Info
Title
Corner Detection Of Gray Level Images Using Gabor Wavelets
Abstract
This paper proposes a novel method for corner detection of gray level images using Gabor wavelets. Wavelet transform is a tool that can provide multi-scale analysis while analyzing the local behavior of a signal. Gabor wavelets are known for their good localization in the time-frequency plane. Furthermore, they provide the shape and orientation information of local structures directly. In the proposed algorithm, the input image is decomposed at several wavelet scales and along several directions. The magnitude along the direction that is orthogonal to the gradient orientation represents the cornerless measurement. The proposed method is efficient since it has good localization, is robust to noise and achieves a high rate of true detection while keeping a low rate of false detection. Simulation results compare the proposed method with the two existing best approaches and show the good performance of the proposed method.
Year
DOI
Venue
2004
10.1109/ICIP.2004.1421653
ICIP: 2004 INTERNATIONAL CONFERENCE ON IMAGE PROCESSING, VOLS 1- 5
Keywords
Field
DocType
gabor wavelets,corner detection,time frequency analysis,wavelet transform,indexing terms,wavelet transforms,time frequency,edge detection
Magnitude (mathematics),Computer vision,Corner detection,Pattern recognition,Gabor wavelet,Computer science,Edge detection,Time–frequency analysis,Artificial intelligence,Gabor transform,Wavelet transform,Wavelet
Conference
ISSN
Citations 
PageRank 
1522-4880
5
0.46
References 
Authors
12
3
Name
Order
Citations
PageRank
Xinting Gao111910.60
Farook Sattar237141.95
Ronda Venkateswarlu325517.03