EDGE-DETECTION IN NOISY IMAGES BASED ON THE COOCCURRENCE MATRIX

An edge detection method for noisy images is proposed based on the co-occurrence matrix. In the proposed technique based on the step-edge model, the gray level information is simply converted into a bit-map, i.e. the uniform and boundary regions of an image are transformed into a binary pattern by normalization using the local mean. In this binary bit-map pattern, 0 and 1 are densely distributed near the boundary region while they are randomly distributed in the uniform region. To detect the boundary region, the co-occurrence matrix on the bit-map is introduced. The effectiveness of the proposed technique is shown via a quantitative performance comparison to the conventional edge detection methods and the simulation results for noisy images are also presented.