Intensity invariant nonlinear correlation filtering for detection of camouflage patterns
Trying it to spot a camouflaged target in a forest far away is hard enough for us. Our naked eyes can only process these much to search and location an unknown target. Hence we need an equipment/ways to provide reliable and accuracy solution to handle this task. Accuracy for most patt...
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sg-ntu-dr.10356-485522023-03-03T20:40:42Z Intensity invariant nonlinear correlation filtering for detection of camouflage patterns Heng, Boon Hua. Qian Kemao School of Computer Engineering DRNTU::Engineering::Computer science and engineering::Computing methodologies::Pattern recognition DRNTU::Engineering::Computer science and engineering::Computing methodologies::Simulation and modeling Trying it to spot a camouflaged target in a forest far away is hard enough for us. Our naked eyes can only process these much to search and location an unknown target. Hence we need an equipment/ways to provide reliable and accuracy solution to handle this task. Accuracy for most pattern recognition techniques is a problem when searching for target in a camouflaged environment under illumination conditions. Different illuminations conditions may cause the correlation values to vary. Consistent is also important so that even with different combination of illumination conditions and camouflaged pattern, results remain similar and not random. This technique does need to know the exact camouflaged pattern but the class of the pattern. In this report, we will look into an algorithm method based on orthonormal vector space basis representation to detect camouflaged in natural environments by Henri H. Arsenault and Pascuala Garcia-Martinez. We will analysis and experiment to determine how efficient it is by simulating the method. Bachelor of Engineering (Computer Engineering) 2012-04-26T03:22:44Z 2012-04-26T03:22:44Z 2012 2012 Final Year Project (FYP) http://hdl.handle.net/10356/48552 en Nanyang Technological University 39 p. application/pdf |
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DRNTU::Engineering::Computer science and engineering::Computing methodologies::Pattern recognition DRNTU::Engineering::Computer science and engineering::Computing methodologies::Simulation and modeling Heng, Boon Hua. Intensity invariant nonlinear correlation filtering for detection of camouflage patterns |
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Trying it to spot a camouflaged target in a forest far away is hard enough for us. Our naked eyes can only process these much to search and location an unknown target. Hence we need an equipment/ways to provide reliable and accuracy solution to handle this task.
Accuracy for most pattern recognition techniques is a problem when searching for target in a camouflaged environment under illumination conditions. Different illuminations conditions may cause the correlation values to vary. Consistent is also important so that even with different combination of illumination conditions and camouflaged pattern, results remain similar and not random. This technique does need to know the exact camouflaged pattern but the class of the pattern.
In this report, we will look into an algorithm method based on orthonormal vector space basis representation to detect camouflaged in natural environments by Henri H. Arsenault and Pascuala Garcia-Martinez. We will analysis and experiment to determine how efficient it is by simulating the method. |
author2 |
Qian Kemao |
author_facet |
Qian Kemao Heng, Boon Hua. |
format |
Final Year Project |
author |
Heng, Boon Hua. |
author_sort |
Heng, Boon Hua. |
title |
Intensity invariant nonlinear correlation filtering for detection of camouflage patterns |
title_short |
Intensity invariant nonlinear correlation filtering for detection of camouflage patterns |
title_full |
Intensity invariant nonlinear correlation filtering for detection of camouflage patterns |
title_fullStr |
Intensity invariant nonlinear correlation filtering for detection of camouflage patterns |
title_full_unstemmed |
Intensity invariant nonlinear correlation filtering for detection of camouflage patterns |
title_sort |
intensity invariant nonlinear correlation filtering for detection of camouflage patterns |
publishDate |
2012 |
url |
http://hdl.handle.net/10356/48552 |
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1759855148484526080 |