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A New regularized minimum error thresholding method

Transactions of Nanjing University of Aeronautics and Astronautics 2015年第4期32卷 355-364页

作者：王保平张研王晓田吴成茂 National Key Laboratory of Science and Technology on UAV Northwestern Polytechnical University School of Electronics Engineering Xi'an University of Posts and Telecommunications

To overcome the shortcoming that the traditional minimum error threshold method can obtain satisfactory image segmentation results only when the object and background of the image strictly obey a certain type of probability distribution,one proposes the regularized minimum error threshold method and treats the traditional minimum error threshold method as its special *** one constructs the discrete probability distribution by using the separation between segmentation threshold and the average gray-scale values of the object and background of the image so as to compute the information energy of the probability *** impact of the regularized parameter selection on the optimal segmentation threshold of the regularized minimum error threshold method is *** verify the effectiveness of the proposed regularized minimum error threshold method,one selects typical grey-scale images and performs segmentation *** segmentation results obtained by the regularized minimum error threshold method are compared with those obtained with the traditional minimum error threshold *** segmentation results and their analysis show that the regularized minimum error threshold method is feasible and produces more satisfactory segmentation results than the minimum error threshold *** does not exert much impact on object acquisition in case of the addition of a certain noise to an ***,the method can meet the requirements for extracting a real object in the noisy environment.

关键词： image processing image segmentation regularized minimum error threshold method informational divergence segmentation threshold

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