A cost optimal parallel algorithm for histogram image matching

This paper presents a parallel algorithm for histogram image template matching using an SIMD array processor with a hypercube interconnection network. For an N×N image and M×M template window, the time complexity is shown to be reduced to O(M+log²M+logN) as compared to O(N²M²) for the sequential algorithm, for the N² processing element (PE) multiprocessor systems. Each PE requires only a small local memory. The algorithm is shown to be cost optimal with total cost of computation is O(N²M+N²log²M+N²logN).