Implementation of a normalized cross-correlation coefficient-based template matching algorithm in number system conversion

In digital image processing, template matching is a technique used for finding or searching for areas of an image that could either match or be similar to the template image. In this study, an algorithm that utilizes both Python programming and the OpenCV library for template matching in number system conversion was successfully demonstrated. Images containing binary numbers were tested for template matching and converted to string. Then, these strings were converted to their respective decimal equivalents. It was found that OpenCV offers a tool that is easy to use for systems that require recognizing patterns of an image. Furthermore, it was observed that the ease of use is accompanied with various limitations such as dependence to pre-processing or having fixed scale, rotation, font, and background color.