A Fast Image Template Matching Algorithm Based on Normalized Cross Correlation

Abstract

Abstract Image matching algorithms based on image gray value are commonly used, which can achieve high matching accuracy. Among them, the Normalized Cross Correlation (NCC) method has high accuracy and strong adaptability, however it has the disadvantages of high computational complexity and slow calculation speed. By using dynamic programming strategy, a fast template matching algorithm based on NCC is proposed in this paper. At the same time, by calculating the cumulative sum of pixel values and the sum of squares of pixel values, and using the down sampling process, the calculation time and complexity are greatly reduced. Experimental results show that the proposed method has the same matching accuracy as the existing algorithms, and further improves the image matching efficiency.