Feature extraction method for human ear image and its application in miner identificatio

In view of problem of big error of existing features extraction method for ear image adopting geometrical shape extraction and algebra extraction, a novel feature extraction method for human ear image was proposed to apply to miner identification. The method uses three-scale canny operator to extract image edges of the helix, and adopts convex hull algorithm to extract key points of ear edge image, uses outer contour search algorithms to extract outer contour of ear image; constructs the ear image feature vector with the length ratio of point to the pole distance of outer ear contour and human ear in epipolar plane, which solves the problem of big error of ear geometry feature. The identification accuracy is 96% with the method to extract human ear image feature for miner identification.