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Image segmentation based on competitive learning

Image segmentation based on competitive learning
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摘要 Image segment is a primary step in image analysis of unexploded ordnance (UXO) detection by ground p enetrating radar (GPR) sensor which is accompanied with a lot of noises and other elements that affect the recognition of real target size. In this paper we bring forward a new theory, that is, we look the weight sets as target vector sets which is the new cues in semi-automatic segmentation to form the final image segmentation. The experiment results show that the measure size of target with our method is much smaller than the size with other methods and close to the real size of target. Image segment is a primary step in image analysis of unexploded ordnance (UXO) detection by ground penetrating radar (GPR) sensor which is accompanied with a lot of noises and other elements that affect the recognition of real target size. In this paper we bring forward a new theory, that is, we look the weight sets as target vector sets which is the new cues in semi-automatic segmentation to form the final image segmentation. The experiment results show that the measure size of target with our method is much smaller than the size with other methods and close to the real size of target.
出处 《Journal of Marine Science and Application》 2004年第1期71-74,共4页 船舶与海洋工程学报(英文版)
基金 Supported by the Natural Science Foundation of Heilongjiang Province (F0201)
关键词 图像分割 竞争性学习 UXO 未爆炸军火探测 GPR 图像信号处理 image segment competitive learning GPR UXO
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