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The multilevel thresholding is an important technique for image processing and pattern recognition. The maximum entropy thresholding has been widely applied in the literature. In this paper, a new multilevel MET algorithm based on the technology of the firefly algorithm is proposed. This proposed method is called the maximum entropy based firefly thresholding method. Four different methods are implemented...
Image thresholding is an important technique for image processing and pattern recognition. In this paper, a new multilevel image thresholding algorithm based on the technology of the honey bee mating optimization (HBMO) is proposed. Three different methods such as the particle swarm optimization (PSO), the hybrid cooperative-comprehensive learning based PSO algorithm (HCOCLPSO) and the fast Otsupsilas...
Image thresholding method based on generalized fuzzy entropy segments the image using the principle that the membership degree of the threshold point is equal to m (0<m<1), better segmentation result can be obtained than that of traditional fuzzy entropy method, especially for images with bad illumination. The main problem of this method is how to determine the parameter m effectively. In this...
Image processing has to deal with many ambiguous situations. Fuzzy set theory is a useful mathematical tool for handling the ambiguity or uncertainty. In order to apply the fuzzy theory, selecting the fuzzy region of membership function is a fundamental and important task. In this paper, a new method of membership function based on fuzzy theory by PSO algorithm optimized was proposed by analyzing...
The contrast of the underwater images is often extraordinarily low due to the ray, assimilating of water, illuminating condition and so on. It is not good for the pretreatment like edge detection and image segmentation. The theory of entropy has been widely used in the pre-process of under water images. However the time-consuming computation is often an obstacle in real time application systems. In...
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