Improved method for local image feature region description

A robust method for local image feature region description was proposed based on the problem of contradiction between performance and dimension of descriptor.First,the local feature region was divided into several subregions according to their intensity order.Then,the method of segmented local featu...

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Main Authors: Ren-huan ZHU, Qing-wei GAO, Yi-xiang LU, Dong SUN
Format: Article
Language:zho
Published: Editorial Department of Journal on Communications 2015-04-01
Series:Tongxin xuebao
Subjects:
Online Access:http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2015089/
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author Ren-huan ZHU
Qing-wei GAO
Yi-xiang LU
Dong SUN
author_facet Ren-huan ZHU
Qing-wei GAO
Yi-xiang LU
Dong SUN
author_sort Ren-huan ZHU
collection DOAJ
description A robust method for local image feature region description was proposed based on the problem of contradiction between performance and dimension of descriptor.First,the local feature region was divided into several subregions according to their intensity order.Then,the method of segmented local feature description based on threshold was used to compute the descriptor,and the method of the weighted texture spectrum was used to cumulate the local descriptor.At last,concatenate the descriptors of every subregion together to get the final descriptor of the interest region.This method combined overall information and local information together,and robust to noise when ensure the dimension of descriptor was small.The experimental results show that the proposed descriptor is not only invariant to monotonic intensity changes and image rotation but also robust to many other geometric and photometric transformations.
format Article
id doaj-art-07e7406a35b942959e1794009df48796
institution Kabale University
issn 1000-436X
language zho
publishDate 2015-04-01
publisher Editorial Department of Journal on Communications
record_format Article
series Tongxin xuebao
spelling doaj-art-07e7406a35b942959e1794009df487962025-01-14T06:46:15ZzhoEditorial Department of Journal on CommunicationsTongxin xuebao1000-436X2015-04-013617918459692666Improved method for local image feature region descriptionRen-huan ZHUQing-wei GAOYi-xiang LUDong SUNA robust method for local image feature region description was proposed based on the problem of contradiction between performance and dimension of descriptor.First,the local feature region was divided into several subregions according to their intensity order.Then,the method of segmented local feature description based on threshold was used to compute the descriptor,and the method of the weighted texture spectrum was used to cumulate the local descriptor.At last,concatenate the descriptors of every subregion together to get the final descriptor of the interest region.This method combined overall information and local information together,and robust to noise when ensure the dimension of descriptor was small.The experimental results show that the proposed descriptor is not only invariant to monotonic intensity changes and image rotation but also robust to many other geometric and photometric transformations.http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2015089/local featurefeature detectionfeature descriptionrotation invariant
spellingShingle Ren-huan ZHU
Qing-wei GAO
Yi-xiang LU
Dong SUN
Improved method for local image feature region description
Tongxin xuebao
local feature
feature detection
feature description
rotation invariant
title Improved method for local image feature region description
title_full Improved method for local image feature region description
title_fullStr Improved method for local image feature region description
title_full_unstemmed Improved method for local image feature region description
title_short Improved method for local image feature region description
title_sort improved method for local image feature region description
topic local feature
feature detection
feature description
rotation invariant
url http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2015089/
work_keys_str_mv AT renhuanzhu improvedmethodforlocalimagefeatureregiondescription
AT qingweigao improvedmethodforlocalimagefeatureregiondescription
AT yixianglu improvedmethodforlocalimagefeatureregiondescription
AT dongsun improvedmethodforlocalimagefeatureregiondescription