Saliency Detection via Fusing Color Contrast and Hash Fingerprint

Saliency detection is a technique for automatically extracting regions of interest from the background and has been widely used in the computer vision field. This study proposes a simple and effective saliency detection method combining color contrast and hash fingerprint. In our solution, the input...

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Main Authors: Yin Lv, Xuanrui Zhang, Yong Wang
Format: Article
Language:English
Published: Wiley 2022-01-01
Series:Journal of Electrical and Computer Engineering
Online Access:http://dx.doi.org/10.1155/2022/9476111
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author Yin Lv
Xuanrui Zhang
Yong Wang
author_facet Yin Lv
Xuanrui Zhang
Yong Wang
author_sort Yin Lv
collection DOAJ
description Saliency detection is a technique for automatically extracting regions of interest from the background and has been widely used in the computer vision field. This study proposes a simple and effective saliency detection method combining color contrast and hash fingerprint. In our solution, the input image is segmented into nonoverlapping superpixels, so as to perform the saliency detection at the region level to reduce computational complexity. A background optimization selection is used to construct an accurate background template. Based on this, a saliency map that highlights the whole salient region is obtained by estimating color contrast. Besides, another saliency map that enhances the salient region while restraining the background is also generated through hash fingerprint matching. Ultimately, the final saliency map can be obtained by fusing the two saliency maps. Comparing the performance with other methods, the proposed algorithm works better even in the presence of complex background or very large salient regions.
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spelling doaj-art-cbfef5ab74da4e82b0ba70bbd1dfc2d32025-08-20T02:19:57ZengWileyJournal of Electrical and Computer Engineering2090-01552022-01-01202210.1155/2022/9476111Saliency Detection via Fusing Color Contrast and Hash FingerprintYin Lv0Xuanrui Zhang1Yong Wang2School of Mechanical Engineering and Electronic InformationSchool of Mechanical Engineering and Electronic InformationSchool of Mechanical Engineering and Electronic InformationSaliency detection is a technique for automatically extracting regions of interest from the background and has been widely used in the computer vision field. This study proposes a simple and effective saliency detection method combining color contrast and hash fingerprint. In our solution, the input image is segmented into nonoverlapping superpixels, so as to perform the saliency detection at the region level to reduce computational complexity. A background optimization selection is used to construct an accurate background template. Based on this, a saliency map that highlights the whole salient region is obtained by estimating color contrast. Besides, another saliency map that enhances the salient region while restraining the background is also generated through hash fingerprint matching. Ultimately, the final saliency map can be obtained by fusing the two saliency maps. Comparing the performance with other methods, the proposed algorithm works better even in the presence of complex background or very large salient regions.http://dx.doi.org/10.1155/2022/9476111
spellingShingle Yin Lv
Xuanrui Zhang
Yong Wang
Saliency Detection via Fusing Color Contrast and Hash Fingerprint
Journal of Electrical and Computer Engineering
title Saliency Detection via Fusing Color Contrast and Hash Fingerprint
title_full Saliency Detection via Fusing Color Contrast and Hash Fingerprint
title_fullStr Saliency Detection via Fusing Color Contrast and Hash Fingerprint
title_full_unstemmed Saliency Detection via Fusing Color Contrast and Hash Fingerprint
title_short Saliency Detection via Fusing Color Contrast and Hash Fingerprint
title_sort saliency detection via fusing color contrast and hash fingerprint
url http://dx.doi.org/10.1155/2022/9476111
work_keys_str_mv AT yinlv saliencydetectionviafusingcolorcontrastandhashfingerprint
AT xuanruizhang saliencydetectionviafusingcolorcontrastandhashfingerprint
AT yongwang saliencydetectionviafusingcolorcontrastandhashfingerprint