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Detection and analyzing the quality of thermal imager for moving object at different ranges
The efficiency of the thermal camera depends on the image quality or detecting and recognizing the target. This research presents a mathematical model that programed in MathCAD to verify the efficiency of the thermal camera (PT-602CZ HD) when the object is in motion at different speeds. The intensit...
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creator | Raheem, Ahmed Fadhil Abdul Raheem, Azhr Abdulzahraa Fuliful, Fadhil Khaddam |
description | The efficiency of the thermal camera depends on the image quality or detecting and recognizing the target. This research presents a mathematical model that programed in MathCAD to verify the efficiency of the thermal camera (PT-602CZ HD) when the object is in motion at different speeds. The intensity distribution in thermal imager was calculated from solving the Bar Spread Function (BSF) at two cases with and without linear motion factor (A) . The values of (A) depend on many factors and the values are determined according to the target velocity (40,60, 80.100 and 120) Km/h. The intensity distributing of the thermal image are calculated for different ranges (150, 300, 500, 750, 1250, 1500, 2000, 2500, 3000, 3500, 3750, 4000, 4250, 4500) m. The results show that the target can be detected and distinguished in the ranges (150, 300) m but the target detects only in the ranges (500, 750) m. If the range of the moving target is larger than 750m the detection and recognition are impossible for this type of thermal camera. Comparing the theoretical results of intensity degradation of the image measured by the thermal camera with the experimental images of moving objects recorded practically at a similar speed in the Ain Al-Tamur area for the holy Karbala city. |
doi_str_mv | 10.1063/5.0114843 |
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This research presents a mathematical model that programed in MathCAD to verify the efficiency of the thermal camera (PT-602CZ HD) when the object is in motion at different speeds. The intensity distribution in thermal imager was calculated from solving the Bar Spread Function (BSF) at two cases with and without linear motion factor (A) . The values of (A) depend on many factors and the values are determined according to the target velocity (40,60, 80.100 and 120) Km/h. The intensity distributing of the thermal image are calculated for different ranges (150, 300, 500, 750, 1250, 1500, 2000, 2500, 3000, 3500, 3750, 4000, 4250, 4500) m. The results show that the target can be detected and distinguished in the ranges (150, 300) m but the target detects only in the ranges (500, 750) m. If the range of the moving target is larger than 750m the detection and recognition are impossible for this type of thermal camera. Comparing the theoretical results of intensity degradation of the image measured by the thermal camera with the experimental images of moving objects recorded practically at a similar speed in the Ain Al-Tamur area for the holy Karbala city.</description><identifier>ISSN: 0094-243X</identifier><identifier>EISSN: 1551-7616</identifier><identifier>DOI: 10.1063/5.0114843</identifier><identifier>CODEN: APCPCS</identifier><language>eng</language><publisher>Melville: American Institute of Physics</publisher><subject>Cameras ; Heat detection ; Image quality ; Moving targets ; Object motion ; Object recognition ; Target detection ; Thermal imaging</subject><ispartof>AIP conference proceedings, 2023, Vol.2414 (1)</ispartof><rights>Author(s)</rights><rights>2023 Author(s). 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Comparing the theoretical results of intensity degradation of the image measured by the thermal camera with the experimental images of moving objects recorded practically at a similar speed in the Ain Al-Tamur area for the holy Karbala city.</description><subject>Cameras</subject><subject>Heat detection</subject><subject>Image quality</subject><subject>Moving targets</subject><subject>Object motion</subject><subject>Object recognition</subject><subject>Target detection</subject><subject>Thermal imaging</subject><issn>0094-243X</issn><issn>1551-7616</issn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2023</creationdate><recordtype>conference_proceeding</recordtype><recordid>eNp9kEtLAzEUhYMoWKsL_0HAnTA1j0kyWUp9QsGNguAiZCY3dcp0Ms2khfrrnaEFdy4uhwsfB76D0DUlM0okvxMzQmle5PwETagQNFOSylM0IUTnGcv55zm66PsVIUwrVUzQ1wMkqFIdWmxbN5xt9j91u8TpG_Bma5s67XHw4xvXtsH12i4hYh8iXofdCIZyNRRgm7CrvYcIbcLRtkvoL9GZt00PV8ecoo-nx_f5S7Z4e36d3y-yjhHOs4J5L0siba6B61JoyG2lCsdlBaVWxHtny1LAIFYBU9KCK6zXTjrnJLiST9HNobeLYbOFPplV2MbBpDdMKVEwJggZqNsD1Vd1sqOx6eKgE_eGEjOOZ4Q5jvcfvAvxDzSd8_wXoiNx3w</recordid><startdate>20230213</startdate><enddate>20230213</enddate><creator>Raheem, Ahmed Fadhil Abdul</creator><creator>Raheem, Azhr Abdulzahraa</creator><creator>Fuliful, Fadhil Khaddam</creator><general>American Institute of Physics</general><scope>8FD</scope><scope>H8D</scope><scope>L7M</scope></search><sort><creationdate>20230213</creationdate><title>Detection and analyzing the quality of thermal imager for moving object at different ranges</title><author>Raheem, Ahmed Fadhil Abdul ; Raheem, Azhr Abdulzahraa ; Fuliful, Fadhil Khaddam</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-p2033-82ff6b06a49e39b59e4ac78d36ceb970ffdabb5e011ce276aed8af9d6ddd6edb3</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2023</creationdate><topic>Cameras</topic><topic>Heat detection</topic><topic>Image quality</topic><topic>Moving targets</topic><topic>Object motion</topic><topic>Object recognition</topic><topic>Target detection</topic><topic>Thermal imaging</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Raheem, Ahmed Fadhil Abdul</creatorcontrib><creatorcontrib>Raheem, Azhr Abdulzahraa</creatorcontrib><creatorcontrib>Fuliful, Fadhil Khaddam</creatorcontrib><collection>Technology Research Database</collection><collection>Aerospace Database</collection><collection>Advanced Technologies Database with Aerospace</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Raheem, Ahmed Fadhil Abdul</au><au>Raheem, Azhr Abdulzahraa</au><au>Fuliful, Fadhil Khaddam</au><au>AL-Baiati, Mohammad N.</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Detection and analyzing the quality of thermal imager for moving object at different ranges</atitle><btitle>AIP conference proceedings</btitle><date>2023-02-13</date><risdate>2023</risdate><volume>2414</volume><issue>1</issue><issn>0094-243X</issn><eissn>1551-7616</eissn><coden>APCPCS</coden><abstract>The efficiency of the thermal camera depends on the image quality or detecting and recognizing the target. This research presents a mathematical model that programed in MathCAD to verify the efficiency of the thermal camera (PT-602CZ HD) when the object is in motion at different speeds. The intensity distribution in thermal imager was calculated from solving the Bar Spread Function (BSF) at two cases with and without linear motion factor (A) . The values of (A) depend on many factors and the values are determined according to the target velocity (40,60, 80.100 and 120) Km/h. The intensity distributing of the thermal image are calculated for different ranges (150, 300, 500, 750, 1250, 1500, 2000, 2500, 3000, 3500, 3750, 4000, 4250, 4500) m. The results show that the target can be detected and distinguished in the ranges (150, 300) m but the target detects only in the ranges (500, 750) m. If the range of the moving target is larger than 750m the detection and recognition are impossible for this type of thermal camera. 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source | American Institute of Physics:Jisc Collections:Transitional Journals Agreement 2021-23 (Reading list) |
subjects | Cameras Heat detection Image quality Moving targets Object motion Object recognition Target detection Thermal imaging |
title | Detection and analyzing the quality of thermal imager for moving object at different ranges |
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