Abstract Exploiting the characteristics of corner, an information
entropy-based corner detection algorithm using the multi-directional
Gabor filters is proposed in this paper. Different from the methods
which detect corners by analyzing plane curve contour shape or
finding for local maxima of curvature, the proposed method combines
with the gray level changing information at edge contour pixels and
pixels around the contour pixels to find corner . Firstly, the Canny
edge operator is used to extract edge map and the gaps in the edge
map are filled. Secondly, the imaginary parts of Gabor filters are
used to smooth the edge pixels and their surrounding pixels along
multi-directions. Finally, the gradient direction information
entropy at the edge pixels is used to detect corners. Experimental
results show that the proposed algorithm attains better detection
performance, higher localization accuracy and noise robustness than
the existing several algorithms.
2015, Vol. 8 
