Infrared dim and small target detecting and tracking method inspired by Human Visual System
•A novel method which is inspired by Human Visual System is proposed in this paper.•This method combines three mechanisms of HVS together.•DOG filter is used to simulate the contrast mechanism.•A Gaussian window is added at a point to simulate the visual attention.•The PID algorithm is first introdu...
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Veröffentlicht in: | Infrared physics & technology 2014-01, Vol.62, p.100-109 |
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creator | Dong, Xiabin Huang, Xinsheng Zheng, Yongbin Shen, Lurong Bai, Shengjian |
description | •A novel method which is inspired by Human Visual System is proposed in this paper.•This method combines three mechanisms of HVS together.•DOG filter is used to simulate the contrast mechanism.•A Gaussian window is added at a point to simulate the visual attention.•The PID algorithm is first introduced to simulate the eye movement of human being.
Detecting and tracking dim and small target in infrared images and videos is one of the most important techniques in many computer vision applications, such as video surveillance and infrared imaging precise guidance. Recently, more and more algorithms based on Human Visual System (HVS) have been proposed to detect and track the infrared dim and small target. In general, HVS concerns at least three mechanisms including contrast mechanism, visual attention and eye movement. However, most of the existing algorithms simulate only a single one of the HVS mechanisms, resulting in many drawbacks of these algorithms. A novel method which combines the three mechanisms of HVS is proposed in this paper. First, a group of Difference of Gaussians (DOG) filters which simulate the contrast mechanism are used to filter the input image. Second, a visual attention, which is simulated by a Gaussian window, is added at a point near the target in order to further enhance the dim small target. This point is named as the attention point. Eventually, the Proportional-Integral-Derivative (PID) algorithm is first introduced to predict the attention point of the next frame of an image which simulates the eye movement of human being. Experimental results of infrared images with different types of backgrounds demonstrate the high efficiency and accuracy of the proposed method to detect and track the dim and small targets. |
doi_str_mv | 10.1016/j.infrared.2013.11.007 |
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Detecting and tracking dim and small target in infrared images and videos is one of the most important techniques in many computer vision applications, such as video surveillance and infrared imaging precise guidance. Recently, more and more algorithms based on Human Visual System (HVS) have been proposed to detect and track the infrared dim and small target. In general, HVS concerns at least three mechanisms including contrast mechanism, visual attention and eye movement. However, most of the existing algorithms simulate only a single one of the HVS mechanisms, resulting in many drawbacks of these algorithms. A novel method which combines the three mechanisms of HVS is proposed in this paper. First, a group of Difference of Gaussians (DOG) filters which simulate the contrast mechanism are used to filter the input image. Second, a visual attention, which is simulated by a Gaussian window, is added at a point near the target in order to further enhance the dim small target. This point is named as the attention point. Eventually, the Proportional-Integral-Derivative (PID) algorithm is first introduced to predict the attention point of the next frame of an image which simulates the eye movement of human being. Experimental results of infrared images with different types of backgrounds demonstrate the high efficiency and accuracy of the proposed method to detect and track the dim and small targets.</description><identifier>ISSN: 1350-4495</identifier><identifier>EISSN: 1879-0275</identifier><identifier>DOI: 10.1016/j.infrared.2013.11.007</identifier><language>eng</language><publisher>Elsevier B.V</publisher><subject>Algorithms ; Computer simulation ; DOG filter ; Eye movements ; Gaussian window ; Human Visual System ; Infrared ; Infrared imagery ; Infrared small target tracking ; PID algorithm ; Proportional integral derivative ; Tracking ; Visual</subject><ispartof>Infrared physics & technology, 2014-01, Vol.62, p.100-109</ispartof><rights>2013 Elsevier B.V.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c345t-bd48c2c4d80c052dba579c4e6a093d12a96987ec6c975bcbff7e200576ffa0a53</citedby><cites>FETCH-LOGICAL-c345t-bd48c2c4d80c052dba579c4e6a093d12a96987ec6c975bcbff7e200576ffa0a53</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://www.sciencedirect.com/science/article/pii/S1350449513002090$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>314,776,780,3536,27903,27904,65309</link.rule.ids></links><search><creatorcontrib>Dong, Xiabin</creatorcontrib><creatorcontrib>Huang, Xinsheng</creatorcontrib><creatorcontrib>Zheng, Yongbin</creatorcontrib><creatorcontrib>Shen, Lurong</creatorcontrib><creatorcontrib>Bai, Shengjian</creatorcontrib><title>Infrared dim and small target detecting and tracking method inspired by Human Visual System</title><title>Infrared physics & technology</title><description>•A novel method which is inspired by Human Visual System is proposed in this paper.•This method combines three mechanisms of HVS together.•DOG filter is used to simulate the contrast mechanism.•A Gaussian window is added at a point to simulate the visual attention.•The PID algorithm is first introduced to simulate the eye movement of human being.
Detecting and tracking dim and small target in infrared images and videos is one of the most important techniques in many computer vision applications, such as video surveillance and infrared imaging precise guidance. Recently, more and more algorithms based on Human Visual System (HVS) have been proposed to detect and track the infrared dim and small target. In general, HVS concerns at least three mechanisms including contrast mechanism, visual attention and eye movement. However, most of the existing algorithms simulate only a single one of the HVS mechanisms, resulting in many drawbacks of these algorithms. A novel method which combines the three mechanisms of HVS is proposed in this paper. First, a group of Difference of Gaussians (DOG) filters which simulate the contrast mechanism are used to filter the input image. Second, a visual attention, which is simulated by a Gaussian window, is added at a point near the target in order to further enhance the dim small target. This point is named as the attention point. Eventually, the Proportional-Integral-Derivative (PID) algorithm is first introduced to predict the attention point of the next frame of an image which simulates the eye movement of human being. Experimental results of infrared images with different types of backgrounds demonstrate the high efficiency and accuracy of the proposed method to detect and track the dim and small targets.</description><subject>Algorithms</subject><subject>Computer simulation</subject><subject>DOG filter</subject><subject>Eye movements</subject><subject>Gaussian window</subject><subject>Human Visual System</subject><subject>Infrared</subject><subject>Infrared imagery</subject><subject>Infrared small target tracking</subject><subject>PID algorithm</subject><subject>Proportional integral derivative</subject><subject>Tracking</subject><subject>Visual</subject><issn>1350-4495</issn><issn>1879-0275</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2014</creationdate><recordtype>article</recordtype><recordid>eNqFkMtOwzAQRS0EEqXwC8hLNgnjJM5jB0JAK1ViwWPDwnLsSXHJo9gOUv8eh5Y1q5mRfe5oDiGXDGIGLL_exKZvrLSo4wRYGjMWAxRHZMbKooogKfhx6FMOUZZV_JScObeBAGaQz8j78sBSbToqe01dJ9uWemnX6KlGj8qbfv375K1Un9PQof8YNDW925qJrXd0MXayp2_GjbKlzzvnsTsnJ41sHV4c6py8Pty_3C2i1dPj8u52Fak04z6qdVaqRGW6BAU80bXkRaUyzCVUqWaJrPKqLFDlqip4reqmKTAB4EXeNBIkT-fkap-7tcPXiM6LzjiFbSt7HEYnGGdhEfAQNyf5_quyg3MWG7G1ppN2JxiIyabYiD-bYrIpGBPBZgBv9iCGQ74NWuGUwV6hDgKUF3ow_0X8AHt4gm0</recordid><startdate>201401</startdate><enddate>201401</enddate><creator>Dong, Xiabin</creator><creator>Huang, Xinsheng</creator><creator>Zheng, Yongbin</creator><creator>Shen, Lurong</creator><creator>Bai, Shengjian</creator><general>Elsevier B.V</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7SP</scope><scope>7U5</scope><scope>8FD</scope><scope>H8D</scope><scope>L7M</scope></search><sort><creationdate>201401</creationdate><title>Infrared dim and small target detecting and tracking method inspired by Human Visual System</title><author>Dong, Xiabin ; Huang, Xinsheng ; Zheng, Yongbin ; Shen, Lurong ; Bai, Shengjian</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c345t-bd48c2c4d80c052dba579c4e6a093d12a96987ec6c975bcbff7e200576ffa0a53</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2014</creationdate><topic>Algorithms</topic><topic>Computer simulation</topic><topic>DOG filter</topic><topic>Eye movements</topic><topic>Gaussian window</topic><topic>Human Visual System</topic><topic>Infrared</topic><topic>Infrared imagery</topic><topic>Infrared small target tracking</topic><topic>PID algorithm</topic><topic>Proportional integral derivative</topic><topic>Tracking</topic><topic>Visual</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Dong, Xiabin</creatorcontrib><creatorcontrib>Huang, Xinsheng</creatorcontrib><creatorcontrib>Zheng, Yongbin</creatorcontrib><creatorcontrib>Shen, Lurong</creatorcontrib><creatorcontrib>Bai, Shengjian</creatorcontrib><collection>CrossRef</collection><collection>Electronics & Communications Abstracts</collection><collection>Solid State and Superconductivity Abstracts</collection><collection>Technology Research Database</collection><collection>Aerospace Database</collection><collection>Advanced Technologies Database with Aerospace</collection><jtitle>Infrared physics & technology</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Dong, Xiabin</au><au>Huang, Xinsheng</au><au>Zheng, Yongbin</au><au>Shen, Lurong</au><au>Bai, Shengjian</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Infrared dim and small target detecting and tracking method inspired by Human Visual System</atitle><jtitle>Infrared physics & technology</jtitle><date>2014-01</date><risdate>2014</risdate><volume>62</volume><spage>100</spage><epage>109</epage><pages>100-109</pages><issn>1350-4495</issn><eissn>1879-0275</eissn><abstract>•A novel method which is inspired by Human Visual System is proposed in this paper.•This method combines three mechanisms of HVS together.•DOG filter is used to simulate the contrast mechanism.•A Gaussian window is added at a point to simulate the visual attention.•The PID algorithm is first introduced to simulate the eye movement of human being.
Detecting and tracking dim and small target in infrared images and videos is one of the most important techniques in many computer vision applications, such as video surveillance and infrared imaging precise guidance. Recently, more and more algorithms based on Human Visual System (HVS) have been proposed to detect and track the infrared dim and small target. In general, HVS concerns at least three mechanisms including contrast mechanism, visual attention and eye movement. However, most of the existing algorithms simulate only a single one of the HVS mechanisms, resulting in many drawbacks of these algorithms. A novel method which combines the three mechanisms of HVS is proposed in this paper. First, a group of Difference of Gaussians (DOG) filters which simulate the contrast mechanism are used to filter the input image. Second, a visual attention, which is simulated by a Gaussian window, is added at a point near the target in order to further enhance the dim small target. This point is named as the attention point. Eventually, the Proportional-Integral-Derivative (PID) algorithm is first introduced to predict the attention point of the next frame of an image which simulates the eye movement of human being. Experimental results of infrared images with different types of backgrounds demonstrate the high efficiency and accuracy of the proposed method to detect and track the dim and small targets.</abstract><pub>Elsevier B.V</pub><doi>10.1016/j.infrared.2013.11.007</doi><tpages>10</tpages></addata></record> |
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subjects | Algorithms Computer simulation DOG filter Eye movements Gaussian window Human Visual System Infrared Infrared imagery Infrared small target tracking PID algorithm Proportional integral derivative Tracking Visual |
title | Infrared dim and small target detecting and tracking method inspired by Human Visual System |
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