Saliency Detection Based on Adaptive Threshold Segmentation and Local Background Clues

被引：3
|
作者：
Tang H. [1 ]
Wu S. [1 ]
Guo Y. [2 ]
Pei Y. [1 ]
机构：
[1] School of Electronics and Information Engineering, Hebei University of Technology, Tianjin
[2] School of Computer Science and Engineering, Hebei University of Technology, Tianjin
来源：
Tang, Hongmei (hmtang2005@163.com) | 1600年 / Science Press卷 / 39期
关键词：
Adaptive threshold; Adjacent color difference; Edge optimization; Local background clues; Saliency detection;
D O I：
10.11999/JEIT160984
中图分类号：
学科分类号：
摘要：
In order to improve the applicability for different types of image and integrity of the results, a saliency detection algorithm is proposed. It combines the adaptive threshold merging with a new background selection strategy. In the segmentation process, the color difference sequence is obtained by the selective fusion of RGB and LAB of adjacent blocks. Adaptive threshold is generated by inverse proportion model of block area parameter. Merging progress is done after the adaptive threshold comparison with the color difference sequence. In the background selection process, background regions are obtained by the local relative position of background-subject-background in the local area. The experimental results are optimized for edge. Compared with other algorithms, the saliency map of two values obtained does not need external threshold algorithm in this paper. Adaptive threshold merging can eliminate the details of objects in complex environments and can focus on the saliency comparison of the same level size objects. © 2017, Science Press. All right reserved.
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页码：1592 / 1598
页数：6
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