Edge detection algorithm for in-pixel lighting via genetic optimization algorithm.

The detection of image edges is a major challenge in image processing and computer vision, since it needs to dispense of unnecessary pixels while preserving significant ones which indicate the image's structure. An optimized algorithm for image edge detection is introduced in this study, which uses a Genetic Optimization (GO) Algorithm to seek out sources of the maximum pixel value to optimally allocate the image edges. The algorithm simulates the evaluation of various values and consists of three operations: selection, crossover operations, and thresholding the optimized value. The community is made up of these evaluations which are conducted at each stage to select the fittest individuals and eliminate the less fit ones. By repeating this process, GO eventually identifies the image edges and eliminates non-edge pixels. The results of the study show that the proposed algorithm successfully addresses the challenges associated with image edge detection. The limitations of the research are also discussed, and potential areas for future research are suggested. This algorithm is expected to be useful for solving complex problems. [ABSTRACT FROM AUTHOR]