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The Study of Randomized Visual Saliency Detection Algorithm

Image segmentation process for high quality visual saliency map is very dependent on the existing visual saliency metrics. It is mostly only get sketchy effect of saliency map, and roughly based visual saliency map will affect the image segmentation results. The paper had presented the randomized vi...

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Detalles Bibliográficos
Autores principales: Chen, Yuantao, Xu, Weihong, Kuang, Fangjun, Gao, Shangbing
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi Publishing Corporation 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3872151/
https://www.ncbi.nlm.nih.gov/pubmed/24382980
http://dx.doi.org/10.1155/2013/380245
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author Chen, Yuantao
Xu, Weihong
Kuang, Fangjun
Gao, Shangbing
author_facet Chen, Yuantao
Xu, Weihong
Kuang, Fangjun
Gao, Shangbing
author_sort Chen, Yuantao
collection PubMed
description Image segmentation process for high quality visual saliency map is very dependent on the existing visual saliency metrics. It is mostly only get sketchy effect of saliency map, and roughly based visual saliency map will affect the image segmentation results. The paper had presented the randomized visual saliency detection algorithm. The randomized visual saliency detection method can quickly generate the same size as the original input image and detailed results of the saliency map. The randomized saliency detection method can be applied to real-time requirements for image content-based scaling saliency results map. The randomization method for fast randomized video saliency area detection, the algorithm only requires a small amount of memory space can be detected detailed oriented visual saliency map, the presented results are shown that the method of visual saliency map used in image after the segmentation process can be an ideal segmentation results.
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spelling pubmed-38721512014-01-01 The Study of Randomized Visual Saliency Detection Algorithm Chen, Yuantao Xu, Weihong Kuang, Fangjun Gao, Shangbing Comput Math Methods Med Research Article Image segmentation process for high quality visual saliency map is very dependent on the existing visual saliency metrics. It is mostly only get sketchy effect of saliency map, and roughly based visual saliency map will affect the image segmentation results. The paper had presented the randomized visual saliency detection algorithm. The randomized visual saliency detection method can quickly generate the same size as the original input image and detailed results of the saliency map. The randomized saliency detection method can be applied to real-time requirements for image content-based scaling saliency results map. The randomization method for fast randomized video saliency area detection, the algorithm only requires a small amount of memory space can be detected detailed oriented visual saliency map, the presented results are shown that the method of visual saliency map used in image after the segmentation process can be an ideal segmentation results. Hindawi Publishing Corporation 2013 2013-12-09 /pmc/articles/PMC3872151/ /pubmed/24382980 http://dx.doi.org/10.1155/2013/380245 Text en Copyright © 2013 Yuantao Chen et al. https://creativecommons.org/licenses/by/3.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Chen, Yuantao
Xu, Weihong
Kuang, Fangjun
Gao, Shangbing
The Study of Randomized Visual Saliency Detection Algorithm
title The Study of Randomized Visual Saliency Detection Algorithm
title_full The Study of Randomized Visual Saliency Detection Algorithm
title_fullStr The Study of Randomized Visual Saliency Detection Algorithm
title_full_unstemmed The Study of Randomized Visual Saliency Detection Algorithm
title_short The Study of Randomized Visual Saliency Detection Algorithm
title_sort study of randomized visual saliency detection algorithm
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3872151/
https://www.ncbi.nlm.nih.gov/pubmed/24382980
http://dx.doi.org/10.1155/2013/380245
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