A two step salient objects extraction framework based on image segmentation and saliency detection

作者：Liu, Qiang; Han, Tao^*; Sun, Yantao; Chu, Zhong; Shen, Bingwen

来源：Multimedia Tools and Applications, 2013, 67(1): 231-247.

DOI：10.1007/s11042-012-1077-1

• Salient objects extraction
• Image segmentation
• Saliency detection
• Framework
• SVM

Salient objects extraction from a still image is a very hot topic, as it owns a lot of useful applications (e.g., image compression, content-based image retrieval, digital watermarking). In this paper, targeted to improve the performance of the extraction approach, we propose a two step salient objects extraction framework based on image segmentation and saliency detection (TIS). Specially, during the first step, the image is segmented into several regions using image segmentation algorithm and the saliency map for the whole image is detected with saliency detection algorithm. In the second step, for each region, some features are extracted for the SVM algorithm to classify the region as a background region or a salient region twice. Experimental results show that our proposed framework can extract the salient objects more precisely and can achieve a good extraction results, compared with previous salient objects extraction methods.

• 出版日期2013-11
• 单位北京交通大学; 华中科技大学