MATLAB Code for Red Eye Detection and Correction Algorithm

This article provides a comprehensive discussion on implementing red eye detection using MATLAB programming. Red eye is a common phenomenon in photographs where subjects' eyes appear reddish due to camera flash reflection. Through MATLAB's image processing capabilities, we can develop efficient algorithms to accurately detect and correct red eye artifacts, thereby enhancing photo quality. In the following sections, we will explore MATLAB code implementation for red eye detection, covering essential toolboxes and technical approaches. The implementation typically involves color space conversion (RGB to HSV), threshold-based segmentation for red color identification, morphological operations for region refinement, and circle detection algorithms for pupil localization. We will provide sample code demonstrating key functions such as imread() for image input, rgb2hsv() for color space transformation, and regionprops() for analyzing detected red regions. Additionally, we'll discuss practical applications of these techniques and their scalability for batch processing large image datasets, including performance optimization strategies using vectorized operations and parallel computing toolbox integration.