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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...
A mechanism involving evolutionary genetic programming (GP) and the expectation maximization algorithm (EM) is proposed to generate feature functions automatically, based on the primitive features, for an image pattern recognition system on the diagnosis of the disease OPMD. Prior to the feature function generation, we introduce a novel technique of the primitive texture feature extraction, which...
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...
Infrared (IR) image segmentation is a key technology of automatic target recognition technology (ATR), which strongly affects the image analysis results. As a global threshold method, the maximum entropy method is often applied in multi-threshold image segmentation, which can get ideal result. However, its time-consuming computation is often an obstacle in real time application systems. In this paper,...
Biometric is the science of measuring human physiological and/ or behavioral characteristics for the purpose of authentication and identification. One of the human's physiological characteristics, palmprint, is gaining popularity among researchers because it is features rich. Palmprint is unique and easy to capture using a conventional digital camera. It does not change much across time. In this paper,...
An important problem in questioned document examination is detection of alterations done by inserting words or additional lines of text. In this paper, we present a statistical pattern recognition driven approach that views it as a two- class problem. Given two sample words, one of which is a suspected alteration, it is necessary to determine if the two belong to the same class or different classes...
This paper proposes a novel approach for rank level fusion which gives improved performance gain verified by experimental results. In the absence of ranked features and instead of using the entire template, we propose using K partitions of the template. The approach proposed in the paper is useful for generating sequential ranks and survivor lists on partitions of template to boost confidence levels...
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