Speed-up Template Matching through Integral Image based Weak Classifiers

Template matching is a widely used pattern recognition method, especially in industrial inspection. However, the computational costs of traditional template matching increase dramatically with both template-and scene imagesize. This makes traditional template matching less useful for many (e.g. real-time) applications. In this paper, we present a method to speed-up template matching. First, candidate match locations are determined using a cascaded blockwise computation of integral image based binary test patterns. Then, traditional template matching is applied at the candidate match locations to determine the best overall match. The results show that the proposed method is fast and robus