Bit-plane extension to a class of intensity-based corner detection algorithms

Corners are important image features whose detection is very important in many computer vision tasks. In this paper we have evaluated the performance of five intensity based corner detectors with the help of a dozen test images, artificial and real, based on six performance measures of which three are proposed by us. We then propose a new approach, using bitplane decomposition, in which a grayscale image is first divided into several bit-planes, and then the original corner detectors are applied on all the bit-planes simultaneously and finally using a threshold, all the higher bit-plane corners are recombined up to the thresholded bit-plane to obtain the final set of corners. Using this approach, we have seen that the performance of the algorithms has improved significantly with respect to both detection and time.