A novel hybrid edge detection technique: ABC-FA

Abstract

Image processing is a vast research field with diversified set of practices utilized in so many application areas such as military, security, medical imaging, machine learning and computer vision based on extracted useful information from any kind of image data. Edges within images are undoubtedly accepted as one of the most significant features providing substantial practical information for various applications working on top of miscellaneous optimization algorithms to achieve better results. Artificial Bee Colony and Firefly algorithms are recently developed optimization algorithms and are used to obtain better results for various problems. In this study, a novel hybrid optimization technique is proposed by combining those algorithms aiming better quality in edge detection on grayscale images. The performance of the proposed algorithm is compared with individual performances of Artificial Bee Colony algorithm and the fundamental edge detection methods. The results are demonstrated that the proposed method is encouraging and also produces meaningful results for similar applications.