Abstract: In this paper, a novel adaptive threshold Sobel edge detection algorithm based on the improved genetic algorithm is proposed to detect edges. Because of the influence of external factors in actual detection process, the result of detection is often not accurate enough when the configured threshold of the target image is far away from the real threshold. Different thresholds of images are calculated by improved genetic algorithm for different images. The calculated threshold is used in edge detection. The experimental results show that the image processed by the improved algorithm has stronger edge continuity. It is shown that proposed algorithm has a better detection effect and applicability than the traditional Sobel algorithm.

Weibin Kong, Jianzhao Chen, Yubin Song, Zhongqing Fang, Xiaofang Yang and Hongyan Zhang. “Sobel Edge Detection Algorithm with Adaptive Threshold based on Improved Genetic Algorithm for Image Processing”. International Journal of Advanced Computer Science and Applications (IJACSA) 14.2 (2023). http://dx.doi.org/10.14569/IJACSA.2023.0140266

@article{Kong2023,
title = {Sobel Edge Detection Algorithm with Adaptive Threshold based on Improved Genetic Algorithm for Image Processing},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2023.0140266},
url = {http://dx.doi.org/10.14569/IJACSA.2023.0140266},
year = {2023},
publisher = {The Science and Information Organization},
volume = {14},
number = {2},
author = {Weibin Kong and Jianzhao Chen and Yubin Song and Zhongqing Fang and Xiaofang Yang and Hongyan Zhang}
}