Corner detection using Gabor-type filtering

In this paper a new corner detection technique using Gabor filters is proposed. It is suitable for both binary and gray level images with varying backgrounds. This technique is based on a scale interaction model, where the difference of two lowpass filters (with different bandwidths) is utilized to extract the corners, line intersections and line endings in the input image. The filtering is done iteratively until the change in the output is below a certain threshold. This technique does not require tracking the boundary and computing the curvature. The important features of the scheme include simplicity, robustness, speed of processing and availability of simple controls to tune the technique for various computer vision applications.