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Forward-looking infrared (FLIR) image segmentation is a key technology in the target recognition and tracking. The FLIR image often contains undulated and non-consistent background. These characteristics make standard segmentation methods ineffective for extracting target. For this reason a method for FLIR image segmentation using support vector machine (SVM) is proposed to extract target. A region...
Segmentation of infrared image is very important in infrared image analysis. Support vector machine (SVM) approach is considered a good candidate because of its good generalization performance, especially when the number of training samples is very small and the dimension of feature space is very high. In this paper, a segmentation algorithm based on SVM for infrared image is presented. The algorithm...
Infrared image segmentation is a very important preparatory work in the target recognition and tracking. Because infrared image has the features of low contrast, high noise and blurring, the segmentation is difficult to carry out. A novel image segmentation method, which utilizes the technique of mutual information and genetic algorithm, is proposed. The initial threshold is chosen by using Otsu algorithm...
Image segmentation is the most important key in tracking processing of infrared imaging precise guidance. For the segmentation of forward-looking infrared (FLIR) images, a new method was proposed, which uses Wiener filter to suppress background and enhance target, then uses the C-V model to perform segmentation. The C-V model was improved on segmentation ability and precision. A new energy constructing...
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