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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2014-01-01
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Series: | Mathematical Problems in Engineering |
Online Access: | http://dx.doi.org/10.1155/2014/826068 |
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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 |
work_keys_str_mv |
AT mengmengzhang frompixelstoregionasalientregiondetectionalgorithmforlocationquantificationimage AT zhiliu frompixelstoregionasalientregiondetectionalgorithmforlocationquantificationimage AT huanzhou frompixelstoregionasalientregiondetectionalgorithmforlocationquantificationimage AT jianwang frompixelstoregionasalientregiondetectionalgorithmforlocationquantificationimage |
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1725218735103410176 |