Fast Correlation Matching in Large ( Edge ) Image Databases

Correlation-based matching methods are known to be very expensive when used on large image databases. In this paper, we will examine ways of speeding up correlation matching by phase-coded ltering. Phase coded ltering is a technique to combine multiple patterns in one lter by assigning complex weights of unit magnitude to the individual patterns and summing them up in a composite lter. Several of the proposed composite lters are based on this idea, such a s t h e Circular Harmonic Component (CHC) lters and the Linear Phase Coeecient Composite (LPCC) lters. We will consider the LPCC(1) lter in isolation and examine ways to improve its performance by assigning the complex weights to the individual patterns in a non-random manner so as to maximize the SNR of the lter w.r.t. the individual patterns. In experiments on a database of 100 to 1000 edge images from the aerial domain we examine the trade-oo between the speed-up (the number of patterns combined in a lter) and unreliability (the number of resulting false matches) of the composite lter. Results indicate that for binary patterns with point densities of about 0.05 we can safely combine more than 20 patterns in the optimized LPCC(1) lter, which represents a speed-up of an order of a magnitude over the brute force approach of matching the individual patterns.