Salient regions detection based on color features

Yanbang Zhang, Lei Guo, Gong Cheng

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

In the paper, we provide a model to detect salient regions by using color features. First, the original image is segmented into superpixels to reduce computational complexity and suppress the disturbance of noise. Second, we select the superpixels in the corner of the image as background prior, and then compute the color contrast features in both Lab color space and the opponency color space. Furthermore, the location information is considered. Next, we employ two-dimension entropy to evaluate the performance of salient maps, and choose appropriate features to fuse. Finally, experimental results are given to show that the proposed model outperforms the some existing models on salient region detection.

Original languageEnglish
Title of host publicationProceedings of the 35th Chinese Control Conference, CCC 2016
EditorsJie Chen, Qianchuan Zhao, Jie Chen
PublisherIEEE Computer Society
Pages4198-4201
Number of pages4
ISBN (Electronic)9789881563910
DOIs
StatePublished - 26 Aug 2016
Event35th Chinese Control Conference, CCC 2016 - Chengdu, China
Duration: 27 Jul 201629 Jul 2016

Publication series

NameChinese Control Conference, CCC
Volume2016-August
ISSN (Print)1934-1768
ISSN (Electronic)2161-2927

Conference

Conference35th Chinese Control Conference, CCC 2016
Country/TerritoryChina
CityChengdu
Period27/07/1629/07/16

Keywords

  • color features
  • saliency region detection
  • two-dimension entropy
  • visual attention

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