Real-time Computation of Krawtchouk Moments on Gray Images Using Block Representation

In the field of image analysis, the discrete orthogonal moments have better image representation capability than the continuous orthogonal moments and geometric moments. Krawtchouk moments are discrete orthogonal moments able to capture the local features of an image. The disadvantage of the Krawtchouk moments is the high computational cost which is increased as higher-order moments are involved in the computations. In this paper, we propose an effective approach for the computation of Krawtchouk moments. The gray image is decomposed in a set of binary images. The most significant binary images are represented using Image Block Representation and their moments are computed fast using block techniques. The least significant binary images are substituted by a constant ideal image called "half-intensity" image, which has known Krawtchouk moment values. The proposed method has low computational error, low computational complexity and under certain conditions, it is able to achieve real-time processing rates.