Systems Engineering and Electronics ›› 2018, Vol. 40 ›› Issue (8): 1693-1701.doi: 10.3969/j.issn.1001-506X.2018.08.04

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Image target segmentation method based on fuzzy Renyi entropy and region growing#br#

LIU Songtao, LIU Zhenxing, JIANG Kanghui   

  1. Department of Information System, Dalian Naval Academy, Dalian 116018, China
  • Online:2018-07-25 Published:2018-07-25

Abstract:

In order to achieve fast and accurate target segmentation of aerial reconnaissance images, a segmentation method based on fuzzy Renyi entropy and region growing is proposed. Firstly, based on the segmentation of Renyi maximum entropy, fuzzy membership function is applied, and fuzzy Renyi entropy is introduced to improve the image segmentation effect. Then, for obtaining the seed points, a saliency detection method based on dual pyramids and feature fusion is presented, and the target core region is generated by morphological open operation using reconstruction and region maximum. Finally, the growing criterion is designed to get the binary mark of image segmentation results, and the region block with the largest overlap on the target〖JP2〗 core region for the target segmentation results selected. The experimental results show that the proposed method can realize the fast and accurate segmentation of ship targets in the aerial reconnaissance images under various complex scenes.

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