Stereo Image Analysis: A New Approach Using Orthogonal Moments

This paper presents the mathematical framework of discrete orthogonal moment functions based on Tchebichef polynomials, and provides the conceptual ideas on applying such moments to the problem of stereopsis. Stereo vision algorithms generally use a set of feature descriptors characterizing the image intensity distribution within a small window centered at the pixel being analyzed, to determine the disparity value, and thereby to estimate the depth of the image point at that pixel. Discrete orthogonal moments have several favorable properties making them good candidates for such applications. Some preliminary results obtained using a window based matching algorithm are presented. Apart from being able to represent independent image features, the capability of discrete orthogonal moments to reconstruct the intensity distribution from a moment set could perhaps be utilized in developing a coarse-to-fine disparity estimation algorithm.