A Modified Harris Corner Detection for Breast IR Image
Harris corner detectors, which depend on strong invariance and a local autocorrelation function, display poor detection performance for infrared (IR) images with low contrast and nonobvious edges. In addition, feature points detected by Harris corner detectors are clustered due to the numerous nonlo...
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| Veröffentlicht in: | Mathematical problems in engineering 2014-01, Vol.2014 (2014), p.1-12 |
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| container_title | Mathematical problems in engineering |
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| creator | Lee, Chia-Yen Wang, Hao-Jen Chen, Chung-Ming Chuang, Ching-Cheng Chang, Yeun-Chung Chou, Nien-Shiang |
| description | Harris corner detectors, which depend on strong invariance and a local autocorrelation function, display poor detection performance for infrared (IR) images with low contrast and nonobvious edges. In addition, feature points detected by Harris corner detectors are clustered due to the numerous nonlocal maxima. This paper proposes a modified Harris corner detector that includes two unique steps for processing IR images in order to overcome the aforementioned problems. Image contrast enhancement based on a generalized form of histogram equalization (HE) combined with adjusting the intensity resolution causes false contours on IR images to acquire obvious edges. Adaptive nonmaximal suppression based on eliminating neighboring pixels avoids the clustered features. Preliminary results show that the proposed method can solve the clustering problem and successfully identify the representative feature points of IR breast images. |
| doi_str_mv | 10.1155/2014/902659 |
| format | Article |
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In addition, feature points detected by Harris corner detectors are clustered due to the numerous nonlocal maxima. This paper proposes a modified Harris corner detector that includes two unique steps for processing IR images in order to overcome the aforementioned problems. Image contrast enhancement based on a generalized form of histogram equalization (HE) combined with adjusting the intensity resolution causes false contours on IR images to acquire obvious edges. Adaptive nonmaximal suppression based on eliminating neighboring pixels avoids the clustered features. Preliminary results show that the proposed method can solve the clustering problem and successfully identify the representative feature points of IR breast images.</description><identifier>ISSN: 1024-123X</identifier><identifier>EISSN: 1563-5147</identifier><identifier>DOI: 10.1155/2014/902659</identifier><language>eng</language><publisher>Cairo, Egypt: Hindawi Puplishing Corporation</publisher><subject>Accuracy ; Algorithms ; Autocorrelation functions ; Automation ; Biomedical engineering ; Breast ; Cameras ; Chemotherapy ; Clustering ; Computer engineering ; Corner detection ; Corners ; Detectors ; Engineering ; Heat ; Image acquisition ; Image contrast ; Image detection ; Image enhancement ; Infrared detectors ; Infrared imagery ; Infrared imaging ; Infrared radiation ; Registration</subject><ispartof>Mathematical problems in engineering, 2014-01, Vol.2014 (2014), p.1-12</ispartof><rights>Copyright © 2014 Chia-Yen Lee et al.</rights><rights>Copyright © 2014 Chia-Yen Lee et al. Chia-Yen Lee et al. 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.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c388t-dd9c20eadcc316244b0c3a200ff1eb9ad72fff01626676207bb50dcdc8ada8cc3</citedby><cites>FETCH-LOGICAL-c388t-dd9c20eadcc316244b0c3a200ff1eb9ad72fff01626676207bb50dcdc8ada8cc3</cites><orcidid>0000-0001-5977-3874 ; 0000-0002-7477-782X</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784,27924,27925</link.rule.ids></links><search><contributor>Yau, Her-Terng</contributor><creatorcontrib>Lee, Chia-Yen</creatorcontrib><creatorcontrib>Wang, Hao-Jen</creatorcontrib><creatorcontrib>Chen, Chung-Ming</creatorcontrib><creatorcontrib>Chuang, Ching-Cheng</creatorcontrib><creatorcontrib>Chang, Yeun-Chung</creatorcontrib><creatorcontrib>Chou, Nien-Shiang</creatorcontrib><title>A Modified Harris Corner Detection for Breast IR Image</title><title>Mathematical problems in engineering</title><description>Harris corner detectors, which depend on strong invariance and a local autocorrelation function, display poor detection performance for infrared (IR) images with low contrast and nonobvious edges. 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Preliminary results show that the proposed method can solve the clustering problem and successfully identify the representative feature points of IR breast images.</description><subject>Accuracy</subject><subject>Algorithms</subject><subject>Autocorrelation functions</subject><subject>Automation</subject><subject>Biomedical engineering</subject><subject>Breast</subject><subject>Cameras</subject><subject>Chemotherapy</subject><subject>Clustering</subject><subject>Computer engineering</subject><subject>Corner detection</subject><subject>Corners</subject><subject>Detectors</subject><subject>Engineering</subject><subject>Heat</subject><subject>Image acquisition</subject><subject>Image contrast</subject><subject>Image detection</subject><subject>Image enhancement</subject><subject>Infrared detectors</subject><subject>Infrared imagery</subject><subject>Infrared imaging</subject><subject>Infrared radiation</subject><subject>Registration</subject><issn>1024-123X</issn><issn>1563-5147</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2014</creationdate><recordtype>article</recordtype><sourceid>RHX</sourceid><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><recordid>eNqF0E1LAzEQBuAgCtbqybOw4EWUtTPZTXb3WOtXoSKIgreQ5kNT2k1Ntoj_3pQVD148zcA8MwwvIccIl4iMjShgOWqActbskAEyXuQMy2o39UDLHGnxuk8OYlwAUGRYDwgfZw9eO-uMzu5lCC5mEx9aE7Jr0xnVOd9m1ofsKhgZu2z6lE1X8s0ckj0rl9Ec_dQhebm9eZ7c57PHu-lkPMtVUdddrnWjKBiplSqQ07KcgyokBbAWzbyRuqLWWkgjzitOoZrPGWilVS21rNPSkJz1d9fBf2xM7MTKRWWWS9kav4kCeYUceVlgoqd_6MJvQpu-EykaWpe8aZqkLnqlgo8xGCvWwa1k-BIIYpuh2GYo-gyTPu_1u2u1_HT_4JMem0SMlb-YAeccim8A6HgY</recordid><startdate>20140101</startdate><enddate>20140101</enddate><creator>Lee, Chia-Yen</creator><creator>Wang, Hao-Jen</creator><creator>Chen, Chung-Ming</creator><creator>Chuang, Ching-Cheng</creator><creator>Chang, Yeun-Chung</creator><creator>Chou, Nien-Shiang</creator><general>Hindawi Puplishing Corporation</general><general>Hindawi Publishing Corporation</general><general>Hindawi Limited</general><scope>ADJCN</scope><scope>AHFXO</scope><scope>RHU</scope><scope>RHW</scope><scope>RHX</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7TB</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>ABJCF</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>CCPQU</scope><scope>CWDGH</scope><scope>DWQXO</scope><scope>FR3</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>JQ2</scope><scope>K7-</scope><scope>KR7</scope><scope>L6V</scope><scope>M7S</scope><scope>P5Z</scope><scope>P62</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PTHSS</scope><orcidid>https://orcid.org/0000-0001-5977-3874</orcidid><orcidid>https://orcid.org/0000-0002-7477-782X</orcidid></search><sort><creationdate>20140101</creationdate><title>A Modified Harris Corner Detection for Breast IR Image</title><author>Lee, Chia-Yen ; Wang, Hao-Jen ; Chen, Chung-Ming ; Chuang, Ching-Cheng ; Chang, Yeun-Chung ; Chou, Nien-Shiang</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c388t-dd9c20eadcc316244b0c3a200ff1eb9ad72fff01626676207bb50dcdc8ada8cc3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2014</creationdate><topic>Accuracy</topic><topic>Algorithms</topic><topic>Autocorrelation functions</topic><topic>Automation</topic><topic>Biomedical engineering</topic><topic>Breast</topic><topic>Cameras</topic><topic>Chemotherapy</topic><topic>Clustering</topic><topic>Computer engineering</topic><topic>Corner detection</topic><topic>Corners</topic><topic>Detectors</topic><topic>Engineering</topic><topic>Heat</topic><topic>Image acquisition</topic><topic>Image contrast</topic><topic>Image detection</topic><topic>Image enhancement</topic><topic>Infrared detectors</topic><topic>Infrared imagery</topic><topic>Infrared imaging</topic><topic>Infrared radiation</topic><topic>Registration</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Lee, Chia-Yen</creatorcontrib><creatorcontrib>Wang, Hao-Jen</creatorcontrib><creatorcontrib>Chen, Chung-Ming</creatorcontrib><creatorcontrib>Chuang, Ching-Cheng</creatorcontrib><creatorcontrib>Chang, Yeun-Chung</creatorcontrib><creatorcontrib>Chou, Nien-Shiang</creatorcontrib><collection>الدوريات العلمية والإحصائية - e-Marefa Academic and Statistical Periodicals</collection><collection>معرفة - المحتوى العربي الأكاديمي المتكامل - e-Marefa Academic Complete</collection><collection>Hindawi Publishing Complete</collection><collection>Hindawi Publishing Subscription Journals</collection><collection>Hindawi Publishing Open Access</collection><collection>CrossRef</collection><collection>Mechanical & Transportation Engineering Abstracts</collection><collection>Technology Research Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>Materials Science & Engineering Collection</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>Advanced Technologies & Aerospace Collection</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>Technology Collection</collection><collection>ProQuest One Community College</collection><collection>Middle East & Africa Database</collection><collection>ProQuest Central Korea</collection><collection>Engineering Research Database</collection><collection>ProQuest Central Student</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Computer Science Collection</collection><collection>Computer Science Database</collection><collection>Civil Engineering Abstracts</collection><collection>ProQuest Engineering Collection</collection><collection>Engineering Database</collection><collection>Advanced Technologies & Aerospace Database</collection><collection>ProQuest Advanced Technologies & Aerospace Collection</collection><collection>Access via ProQuest (Open Access)</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>Engineering Collection</collection><jtitle>Mathematical problems in engineering</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Lee, Chia-Yen</au><au>Wang, Hao-Jen</au><au>Chen, Chung-Ming</au><au>Chuang, Ching-Cheng</au><au>Chang, Yeun-Chung</au><au>Chou, Nien-Shiang</au><au>Yau, Her-Terng</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>A Modified Harris Corner Detection for Breast IR Image</atitle><jtitle>Mathematical problems in engineering</jtitle><date>2014-01-01</date><risdate>2014</risdate><volume>2014</volume><issue>2014</issue><spage>1</spage><epage>12</epage><pages>1-12</pages><issn>1024-123X</issn><eissn>1563-5147</eissn><abstract>Harris corner detectors, which depend on strong invariance and a local autocorrelation function, display poor detection performance for infrared (IR) images with low contrast and nonobvious edges. In addition, feature points detected by Harris corner detectors are clustered due to the numerous nonlocal maxima. This paper proposes a modified Harris corner detector that includes two unique steps for processing IR images in order to overcome the aforementioned problems. Image contrast enhancement based on a generalized form of histogram equalization (HE) combined with adjusting the intensity resolution causes false contours on IR images to acquire obvious edges. Adaptive nonmaximal suppression based on eliminating neighboring pixels avoids the clustered features. 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| source | Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals; Wiley Online Library (Open Access Collection); Alma/SFX Local Collection |
| subjects | Accuracy Algorithms Autocorrelation functions Automation Biomedical engineering Breast Cameras Chemotherapy Clustering Computer engineering Corner detection Corners Detectors Engineering Heat Image acquisition Image contrast Image detection Image enhancement Infrared detectors Infrared imagery Infrared imaging Infrared radiation Registration |
| title | A Modified Harris Corner Detection for Breast IR Image |
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