Linear and Quadratic PSO Based Color Space Conversion for Sea Target Detection
Year
: 2010
Abstract: Sea target detection is an important goal for
military purpose and navigation. A new nonlinear quadratic
transform is presented to generate target-based color space
(TCS) for sea target detection. RGB color space is converted to
TCS through a 3*3 matrix, using quadratic transformation.
PSO algorithm is used for maximum differentiation between
target and non-target clusters which are classified with FCM
clustering method. The task of PSO is to minimize the Error
value produced by FCM classifier. Experimental results show
the ability of the new method in finding sea targets in color
images. The superiority of the TCS space to the relative
previous works and other color spaces is conspicuous.
military purpose and navigation. A new nonlinear quadratic
transform is presented to generate target-based color space
(TCS) for sea target detection. RGB color space is converted to
TCS through a 3*3 matrix, using quadratic transformation.
PSO algorithm is used for maximum differentiation between
target and non-target clusters which are classified with FCM
clustering method. The task of PSO is to minimize the Error
value produced by FCM classifier. Experimental results show
the ability of the new method in finding sea targets in color
images. The superiority of the TCS space to the relative
previous works and other color spaces is conspicuous.
Keyword(s):
Quadratic transformation,Color space,Sea
target detection,Particle Swarm Optimization,Fuzzy C-Mean
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Linear and Quadratic PSO Based Color Space Conversion for Sea Target Detection
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| contributor author | S. Mirghasemi | en |
| contributor author | هادی صدوقی یزدی | en |
| contributor author | M. Lotfizad | en |
| contributor author | Hadi Sadoghi Yazdi | fa |
| date accessioned | 2020-06-06T14:26:52Z | |
| date available | 2020-06-06T14:26:52Z | |
| date issued | 2010 | |
| identifier uri | http://libsearch.um.ac.ir:80/fum/handle/fum/3397032?locale-attribute=en | |
| description abstract | Sea target detection is an important goal for military purpose and navigation. A new nonlinear quadratic transform is presented to generate target-based color space (TCS) for sea target detection. RGB color space is converted to TCS through a 3*3 matrix, using quadratic transformation. PSO algorithm is used for maximum differentiation between target and non-target clusters which are classified with FCM clustering method. The task of PSO is to minimize the Error value produced by FCM classifier. Experimental results show the ability of the new method in finding sea targets in color images. The superiority of the TCS space to the relative previous works and other color spaces is conspicuous. | en |
| language | English | |
| title | Linear and Quadratic PSO Based Color Space Conversion for Sea Target Detection | en |
| type | Journal Paper | |
| contenttype | External Fulltext | |
| subject keywords | Quadratic transformation | en |
| subject keywords | Color space | en |
| subject keywords | Sea target detection | en |
| subject keywords | Particle Swarm Optimization | en |
| subject keywords | Fuzzy C-Mean | en |
| journal title | International Journal of Computer and Electrical Engineering | fa |
| pages | 111-118 | |
| journal volume | 2 | |
| journal issue | 1 | |
| identifier link | https://profdoc.um.ac.ir/paper-abstract-1015671.html | |
| identifier articleid | 1015671 |