Optimization of color design for military camouflage in CIELAB color space
The assessment of military camouflage is a key consideration in the modern military field. Traditionally, the assessment relies on traditional human visual detection tests because a large scale multi‐level and multi‐factor experiments are time‐ and resource‐consuming. One aspect of camouflage assess...
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Veröffentlicht in: | Color research and application 2019-06, Vol.44 (3), p.367-380 |
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description | The assessment of military camouflage is a key consideration in the modern military field. Traditionally, the assessment relies on traditional human visual detection tests because a large scale multi‐level and multi‐factor experiments are time‐ and resource‐consuming. One aspect of camouflage assessment, to which this current study pertains, entails improving upon or “enhancing” an existing or “selected” design. The current study presents a new and practical approach for enhancing the selected military camouflage by utilizing response surface methodology (RSM) of %L*, %a*, and %b* in CIELAB color space. Ten participants were recruited to evaluate 35 variations of %L*, %a*, and %b* on camouflage similarity index (CSI) and reaction time (RT). Based on RSM, the optimum combination occurs at L*: 61.4966, a*: −5.6505, and b*: 10.5114. In addition, a predictive algorithm to calculate the optimum shift of %L*, %a*, and %b* from the original camouflage to the improved camouflage derived from RSM is also proposed. The optimum shift occurs at −25%L*, −55%a*, and + 80%b*. In the end, a new design guideline is proposed for the enhancement of selected military camouflage, which adopts the present study's research findings. |
doi_str_mv | 10.1002/col.22352 |
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Traditionally, the assessment relies on traditional human visual detection tests because a large scale multi‐level and multi‐factor experiments are time‐ and resource‐consuming. One aspect of camouflage assessment, to which this current study pertains, entails improving upon or “enhancing” an existing or “selected” design. The current study presents a new and practical approach for enhancing the selected military camouflage by utilizing response surface methodology (RSM) of %L*, %a*, and %b* in CIELAB color space. Ten participants were recruited to evaluate 35 variations of %L*, %a*, and %b* on camouflage similarity index (CSI) and reaction time (RT). Based on RSM, the optimum combination occurs at L*: 61.4966, a*: −5.6505, and b*: 10.5114. In addition, a predictive algorithm to calculate the optimum shift of %L*, %a*, and %b* from the original camouflage to the improved camouflage derived from RSM is also proposed. The optimum shift occurs at −25%L*, −55%a*, and + 80%b*. In the end, a new design guideline is proposed for the enhancement of selected military camouflage, which adopts the present study's research findings.</description><identifier>ISSN: 0361-2317</identifier><identifier>EISSN: 1520-6378</identifier><identifier>DOI: 10.1002/col.22352</identifier><language>eng</language><publisher>Hoboken, USA: John Wiley & Sons, Inc</publisher><subject>Algorithms ; Camouflage ; CIELAB ; Color ; Design optimization ; Military ; military camouflage ; Reaction time ; Response surface methodology ; target search</subject><ispartof>Color research and application, 2019-06, Vol.44 (3), p.367-380</ispartof><rights>2019 Wiley Periodicals, Inc.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c3632-3b59a07df6b4752430610e24ae933ca9716469ce219e3abdb0f3868d4ac28ce03</citedby><cites>FETCH-LOGICAL-c3632-3b59a07df6b4752430610e24ae933ca9716469ce219e3abdb0f3868d4ac28ce03</cites><orcidid>0000-0003-3535-9657</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://onlinelibrary.wiley.com/doi/pdf/10.1002%2Fcol.22352$$EPDF$$P50$$Gwiley$$H</linktopdf><linktohtml>$$Uhttps://onlinelibrary.wiley.com/doi/full/10.1002%2Fcol.22352$$EHTML$$P50$$Gwiley$$H</linktohtml><link.rule.ids>314,776,780,1411,27903,27904,45553,45554</link.rule.ids></links><search><creatorcontrib>Lin, Chiuhsiang Joe</creatorcontrib><creatorcontrib>Prasetyo, Yogi Tri</creatorcontrib><creatorcontrib>Siswanto, Nio Dolly</creatorcontrib><creatorcontrib>Jiang, Bernard C.</creatorcontrib><title>Optimization of color design for military camouflage in CIELAB color space</title><title>Color research and application</title><description>The assessment of military camouflage is a key consideration in the modern military field. Traditionally, the assessment relies on traditional human visual detection tests because a large scale multi‐level and multi‐factor experiments are time‐ and resource‐consuming. One aspect of camouflage assessment, to which this current study pertains, entails improving upon or “enhancing” an existing or “selected” design. The current study presents a new and practical approach for enhancing the selected military camouflage by utilizing response surface methodology (RSM) of %L*, %a*, and %b* in CIELAB color space. Ten participants were recruited to evaluate 35 variations of %L*, %a*, and %b* on camouflage similarity index (CSI) and reaction time (RT). Based on RSM, the optimum combination occurs at L*: 61.4966, a*: −5.6505, and b*: 10.5114. In addition, a predictive algorithm to calculate the optimum shift of %L*, %a*, and %b* from the original camouflage to the improved camouflage derived from RSM is also proposed. The optimum shift occurs at −25%L*, −55%a*, and + 80%b*. In the end, a new design guideline is proposed for the enhancement of selected military camouflage, which adopts the present study's research findings.</description><subject>Algorithms</subject><subject>Camouflage</subject><subject>CIELAB</subject><subject>Color</subject><subject>Design optimization</subject><subject>Military</subject><subject>military camouflage</subject><subject>Reaction time</subject><subject>Response surface methodology</subject><subject>target search</subject><issn>0361-2317</issn><issn>1520-6378</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2019</creationdate><recordtype>article</recordtype><recordid>eNp1kDFPwzAQhS0EEqUw8A8iMTGkPfsSOxlLVKAoUhaYLcdxKldJHOJUqPx6AunKdDd89969R8g9hRUFYGvtmhVjGLMLsqAxg5CjSC7JApDTkCEV1-TG-wMAxJiIBXkr-tG29luN1nWBq4NJwA1BZbzdd0E9ra1t7KiGU6BV6451o_YmsF2Q7bb55umM-15pc0uuatV4c3eeS_LxvH3PXsO8eNllmzzUyJGFWMapAlHVvIxEzCIETsGwSJkUUatUUB7xVBtGU4OqrEqoMeFJFSnNEm0Al-Rh1u0H93k0fpQHdxy6yVIyBiAojShO1ONM6cF5P5ha9oNtpxySgvytSk6vy7-qJnY9s1-2Maf_QZkV-XzxA1tvaP0</recordid><startdate>201906</startdate><enddate>201906</enddate><creator>Lin, Chiuhsiang Joe</creator><creator>Prasetyo, Yogi Tri</creator><creator>Siswanto, Nio Dolly</creator><creator>Jiang, Bernard C.</creator><general>John Wiley & Sons, Inc</general><general>Wiley Subscription Services, Inc</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7U5</scope><scope>8FD</scope><scope>L7M</scope><orcidid>https://orcid.org/0000-0003-3535-9657</orcidid></search><sort><creationdate>201906</creationdate><title>Optimization of color design for military camouflage in CIELAB color space</title><author>Lin, Chiuhsiang Joe ; Prasetyo, Yogi Tri ; Siswanto, Nio Dolly ; Jiang, Bernard C.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c3632-3b59a07df6b4752430610e24ae933ca9716469ce219e3abdb0f3868d4ac28ce03</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2019</creationdate><topic>Algorithms</topic><topic>Camouflage</topic><topic>CIELAB</topic><topic>Color</topic><topic>Design optimization</topic><topic>Military</topic><topic>military camouflage</topic><topic>Reaction time</topic><topic>Response surface methodology</topic><topic>target search</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Lin, Chiuhsiang Joe</creatorcontrib><creatorcontrib>Prasetyo, Yogi Tri</creatorcontrib><creatorcontrib>Siswanto, Nio Dolly</creatorcontrib><creatorcontrib>Jiang, Bernard C.</creatorcontrib><collection>CrossRef</collection><collection>Solid State and Superconductivity Abstracts</collection><collection>Technology Research Database</collection><collection>Advanced Technologies Database with Aerospace</collection><jtitle>Color research and application</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Lin, Chiuhsiang Joe</au><au>Prasetyo, Yogi Tri</au><au>Siswanto, Nio Dolly</au><au>Jiang, Bernard C.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Optimization of color design for military camouflage in CIELAB color space</atitle><jtitle>Color research and application</jtitle><date>2019-06</date><risdate>2019</risdate><volume>44</volume><issue>3</issue><spage>367</spage><epage>380</epage><pages>367-380</pages><issn>0361-2317</issn><eissn>1520-6378</eissn><abstract>The assessment of military camouflage is a key consideration in the modern military field. Traditionally, the assessment relies on traditional human visual detection tests because a large scale multi‐level and multi‐factor experiments are time‐ and resource‐consuming. One aspect of camouflage assessment, to which this current study pertains, entails improving upon or “enhancing” an existing or “selected” design. The current study presents a new and practical approach for enhancing the selected military camouflage by utilizing response surface methodology (RSM) of %L*, %a*, and %b* in CIELAB color space. Ten participants were recruited to evaluate 35 variations of %L*, %a*, and %b* on camouflage similarity index (CSI) and reaction time (RT). Based on RSM, the optimum combination occurs at L*: 61.4966, a*: −5.6505, and b*: 10.5114. In addition, a predictive algorithm to calculate the optimum shift of %L*, %a*, and %b* from the original camouflage to the improved camouflage derived from RSM is also proposed. The optimum shift occurs at −25%L*, −55%a*, and + 80%b*. In the end, a new design guideline is proposed for the enhancement of selected military camouflage, which adopts the present study's research findings.</abstract><cop>Hoboken, USA</cop><pub>John Wiley & Sons, Inc</pub><doi>10.1002/col.22352</doi><tpages>14</tpages><orcidid>https://orcid.org/0000-0003-3535-9657</orcidid></addata></record> |
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subjects | Algorithms Camouflage CIELAB Color Design optimization Military military camouflage Reaction time Response surface methodology target search |
title | Optimization of color design for military camouflage in CIELAB color space |
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