Image Point Feature Extraction Algorithm of Circumferential Binary Descriptor
Feature point descriptors play an important role in feature extracting,image recognition and detection.For the large computation of gradient direction histogram descriptors such as SIFT etc.and the binary descriptors' defect that could not match the mirrored image very well such as ORB etc.,an image point feature extraction algorithm of circumferential binary descriptor (CBD) is proposed.First,set up the image pyramid by the 1∶1.2 ratio,Gaussian blur each image layer,detect the feature points with FAST detector.Then,the binary image's centroid algorithm is given to compute the orientation of the feature points.With this method the computation speed is improved.Last,CBD is proposed to solve the problem that the other descriptors couldn't match mirrored image effectively.The experimental results show that CBD has a better invariance on mirror image,a better adaptability and a higher inlier point percentage.
image recognitioncircumferential binary descriptorimage centroidmirror invariancefeature match
NETL
NSTL
万方数据
维普
