Stitching Two Consecutive Images Using Template Matching Algorithm

In the field of computer vision, template matching represents a fundamental image processing technique. This algorithm is primarily employed to stitch two adjacent images together, enabling the display of a complete scene within a single composite image. The template matching algorithm operates by comparing similar regions across two images and subsequently merging them. Implementation typically involves calculating similarity metrics (such as cross-correlation or sum of squared differences) between a template from one image and various regions of the target image, then identifying the position with maximum similarity for alignment.

This technique finds applications across multiple domains including medical image processing, machine vision systems, and natural image manipulation. In practical code implementation, key functions often involve OpenCV's matchTemplate() method for similarity calculation and minMaxLoc() for peak detection. The algorithm serves as a crucial component in computer vision research, particularly in panorama creation and image registration tasks where precise alignment is essential.