Efficient Cellular Automata Algorithm for Template Matching

Template matching plays an important role in the field of Artificial Intelligence (AI) and it has been used in many applications related to computer vision and image processing such as object recognition and industrial inspection. The main objective of this study was to introduce an appropriate template matching algorithm to enhance the performance of template matching system. The investigation was based on using Cellular Automata with Rule 170 (CA-R170). The main idea of the proposed technique was based on eliminating some of the undesirable area in the binary source images and their corresponding binary template images. The experimental investigations used two sets of color and gray scale images with different sizes and illumination. Experimental results showed that the proposed method can significantly improve the accuracy and execution time of template matching system.