From Pixels to Region: A Salient Region Detection Algorithm for Location-Quantification Image

Image saliency detection has become increasingly important with the development of intelligent identification and machine vision technology. This process is essential for many image processing algorithms such as image retrieval, image segmentation, image recognition, and adaptive image compression....

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Main Authors: Mengmeng Zhang, Zhi Liu, Huan Zhou, Jian Wang
Format: Article
Language:English
Published: Hindawi Limited 2014-01-01
Series:Mathematical Problems in Engineering
Online Access:http://dx.doi.org/10.1155/2014/826068
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spelling doaj-14da848b0394437baf63cfc76fb07f1e2020-11-25T00:59:07ZengHindawi LimitedMathematical Problems in Engineering1024-123X1563-51472014-01-01201410.1155/2014/826068826068From Pixels to Region: A Salient Region Detection Algorithm for Location-Quantification ImageMengmeng Zhang0Zhi Liu1Huan Zhou2Jian Wang3College of Information Engineering, North China University of Technology, No. 5 Jinyuanzhuang Road, Shijingshan District, Beijing 100144, ChinaCollege of Information Engineering, North China University of Technology, No. 5 Jinyuanzhuang Road, Shijingshan District, Beijing 100144, ChinaCollege of Information Engineering, North China University of Technology, No. 5 Jinyuanzhuang Road, Shijingshan District, Beijing 100144, ChinaCollege of Information Engineering, North China University of Technology, No. 5 Jinyuanzhuang Road, Shijingshan District, Beijing 100144, ChinaImage saliency detection has become increasingly important with the development of intelligent identification and machine vision technology. This process is essential for many image processing algorithms such as image retrieval, image segmentation, image recognition, and adaptive image compression. We propose a salient region detection algorithm for full-resolution images. This algorithm analyzes the randomness and correlation of image pixels and pixel-to-region saliency computation mechanism. The algorithm first obtains points with more saliency probability by using the improved smallest univalue segment assimilating nucleus operator. It then reconstructs the entire saliency region detection by taking these points as reference and combining them with image spatial color distribution, as well as regional and global contrasts. The results for subjective and objective image saliency detection show that the proposed algorithm exhibits outstanding performance in terms of technology indices such as precision and recall rates.http://dx.doi.org/10.1155/2014/826068
collection DOAJ
language English
format Article
sources DOAJ
author Mengmeng Zhang
Zhi Liu
Huan Zhou
Jian Wang
spellingShingle Mengmeng Zhang
Zhi Liu
Huan Zhou
Jian Wang
From Pixels to Region: A Salient Region Detection Algorithm for Location-Quantification Image
Mathematical Problems in Engineering
author_facet Mengmeng Zhang
Zhi Liu
Huan Zhou
Jian Wang
author_sort Mengmeng Zhang
title From Pixels to Region: A Salient Region Detection Algorithm for Location-Quantification Image
title_short From Pixels to Region: A Salient Region Detection Algorithm for Location-Quantification Image
title_full From Pixels to Region: A Salient Region Detection Algorithm for Location-Quantification Image
title_fullStr From Pixels to Region: A Salient Region Detection Algorithm for Location-Quantification Image
title_full_unstemmed From Pixels to Region: A Salient Region Detection Algorithm for Location-Quantification Image
title_sort from pixels to region: a salient region detection algorithm for location-quantification image
publisher Hindawi Limited
series Mathematical Problems in Engineering
issn 1024-123X
1563-5147
publishDate 2014-01-01
description Image saliency detection has become increasingly important with the development of intelligent identification and machine vision technology. This process is essential for many image processing algorithms such as image retrieval, image segmentation, image recognition, and adaptive image compression. We propose a salient region detection algorithm for full-resolution images. This algorithm analyzes the randomness and correlation of image pixels and pixel-to-region saliency computation mechanism. The algorithm first obtains points with more saliency probability by using the improved smallest univalue segment assimilating nucleus operator. It then reconstructs the entire saliency region detection by taking these points as reference and combining them with image spatial color distribution, as well as regional and global contrasts. The results for subjective and objective image saliency detection show that the proposed algorithm exhibits outstanding performance in terms of technology indices such as precision and recall rates.
url http://dx.doi.org/10.1155/2014/826068
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AT huanzhou frompixelstoregionasalientregiondetectionalgorithmforlocationquantificationimage
AT jianwang frompixelstoregionasalientregiondetectionalgorithmforlocationquantificationimage
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