共查询到5条相似文献,搜索用时 0 毫秒
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Quan Yujuan Li Shiguang 《保鲜与加工》1998,(1):77-81
In this paper,a new image reconstruction algorithm named maximum entropy reprojecting is developed for missing projection data from some objects are opaque for parts of ray.The results of comparing simulation experiments on the general computer indicate that the quality of reconstructed images by the new algorithm are much better than the tradional maximum entropy algorithm.So the algorithm has reliable propect in application. 相似文献
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The Recursive Orthogonal Least Squares (ROLS) algorithm is applied to train Radial Basis Function Neural Network (RBFNN) when modeling, so as to save large memory and computational efforts. Using the information available from the trained network with ROLS algorithm, the effective centers of network can be obtained by adopting backward selection algorithm, which achieve acceptable accuracy with significant reduction of network structure. The results of simulation and experimentation show that the algorithm is efficient and useful. 相似文献
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By the definition and interpretation of directional elemental pixel sets, a method for getting the directional image from the binary fingerprint image using the statistic characteristics of DEPS is presented in this paper. This method is better than traditional methods in processing speed, computing complexity and resisting noises. The directional image got by this method is used to the matching of ridges frame in a fingerprint verification system, and the testing result shows that the method is effective. 相似文献
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[Objective] The aim of this study was to improve the cotton image segmentation accuracy in a picking robot image processing system. [Method] An image segmentation algorithm based on a fusion method of Markov random field and quantum particle swarm optimization clustering was proposed. The process of the proposed algorithm is as follows: first, transform the RGB (red, green, blue) images into grayscale; second, use it to segment these images; finally, the threshold of the connected area is set on the basis of the segmented image to obtain the target area. Then, the cotton front image and the cotton side image are selected from the images collected from different angles. The segmentation experiment was carried out by using this algorithm, and compared with the Otsu algorithm, the fuzzy C-means algorithm, the quantum particle swarm image segmentation algorithm and the Markov random field image segmentation algorithm. [Result] The results showed that the segmentation accuracy and peak signal to noise ratio of the proposed algorithm were 98.94% and 77.48 dB. When compared with the Otsu algorithm, fuzzy C-means algorithm, quantum particle swarm optimization algorithm and Markov random field algorithm, the average segmentation accuracy and peak signal to noise ratio of the proposed algorithm increased by 2.47%–4.56%, and 9.81–13.11 dB, respectively. [Conclusion] The proposed algorithm had higher segmentation accuracy and higher peak signal to noise ratio than the other algorithms tested. 相似文献