关键词: 图像分割, 目标检测, Grabcut算法, 人工目标, 微分计盒算法, 图割

Abstract: In view of the disadvantages of traditional Grabcut algorithm rely on human interaction with low efficiency in segmentation, an improved Grabcut algorithm based on the fast differential box-counting method is proposed. It can segment the artificial targets under the complex natural background autonomously. The contour of the artificial targets is detected through fast differential box-counting method, then the initial rectangle and the parameters of Gaussian Mixture Model needed in the Grabcut can be obtained. Utilizing the min cut method to segment the pixels of image, and the target is segmented by energy minimization through several iterations. Experimental results show that the proposed algorithm can segment the artificial target relatively complete under the complex natural background, and can reserve the target’s original information sufficiently.

Key words: image segmentation, target detection, Grabcut algorithin, artificial target, differential box-counting, graph cut