An Edge Detection Method for UAV Image Based on the Enhancing ABC

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Dujin Liu, Chengfu Yang, Xiang Hou

Abstract

In this paper, we propose a novel ABC method called as EABC to improve the efficiency and quality for color UAV image edge detection based on quaternion. We propose a RGB image pixel as a pure quaternion form and applying the principle of rotation quaternion to determine the edge points of the color UAV image. For the artificial bee colony algorithm, two new search equations are presented to generate candidate solutions in the employed bee phase and the onlookers phase, respectively. Then an enhancing artificial bee colony algorithm (EABC) is proposed. Further, a more reasonable ABC parameters is proposed to improve the performance of ABC. Finally, we combine the advantages of quaternion-based color UAV image and enhancing artificial bee colony algorithm to develop color UAV image edge detection. By comparing the performance and computing time processing different images, the proposed method has superior performance which not only provides the best color UAV image edge detection results but also yields better color UAV image quality com-pared to other widely used algorithm.

Article Details

How to Cite
Dujin Liu, Chengfu Yang, Xiang Hou. (2021). An Edge Detection Method for UAV Image Based on the Enhancing ABC. CONVERTER, 2021(6), 362-374. Retrieved from https://converter-magazine.info/index.php/converter/article/view/400
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