Search - matlab image

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[matlab] Matla--Image2 DL : 0: MATLAB图像处理中的实力应用，在文字识别，车牌识别中有较为广泛的应用，第2部分-MATLAB image processing in the strength of applications, in character recognition, license plate recognition to have a fairly wide range of applications, Part 2
Date : Size : 875kb User : nash
[AI-NN-PR] Neural-Network-pattern-recognition DL : 0: 根据神经网络的算法对三幅训练图像和测试图像进行识别。-According to neural network training algorithm for three test images and image recognition.
Date : Size : 43kb User : xjzhang101
[matlab] gabortb-v0.4.1.tar DL : 0: 外国人写matlab 的gobor特征运算工具箱，包括一，二维gobor特征提取工具。-Matlab Toolbox for Gabor Features in Signal and Image Processing. v0.4.1
Date : Size : 44kb User : 周简单
[matlab] edge_detect DL : 0: 利用matlab对图像进行灰度调整、拉伸处理和边缘检测-Use matlab image grayscale adjustment, stretch processing and edge detection
Date : Size : 1kb User : zhang
[matlab] matlab-CA DL : 0: matlab的元胞自动机程序的源代码,胞自动机程序状态演化规则 ①如果一个元胞的状态是0,则当它有状态为1的邻元时,该元胞的状态以概率a×b变为1,并且当它的临域中状态为1的邻元越多,其状态转变为1的概率越大 ②如果一个元胞的状态是1,则该元胞的状态保持不变。初始传播者位于中心单元格25×25处取50×50的网格，临域为Moore型，经过50个仿真时钟,知识传播结果的模拟图 -matlab Cellular Automata procedure source code, cellular automata evolution rules of procedure state ① If a cell' s state is 0, then when it has a status of one element of the neighborhood, the cellular state to the probability of a × b into one, and when it' s Pro domain status is one more element of the neighborhood, its status into a greater probability of 1 ② If a cell' s state is 1, the cellular status remains unchanged. Initial spreaders center cell 25 × 25 obtain 50 × 50 grid, the Pro domain for the Moore-type, after 50 simulation clock, the dissemination of knowledge of the simulation results of Figure
Date : Size : 1kb User : 袁逸扬
[Compress-Decompress algrithms] haffuman DL : 1: 图像处理中压缩编码部分的霍夫曼编码应用实例：MATLAB版源代码-Image Processing coding part of the Huffman code application examples: MATLAB version of the source code
Date : Size : 1kb User : 刘兰芳
[matlab] travai1 DL : 0: Matlab code for encoding an unwrapping phase InSAR image based on Markov Random field
Date : Size : 7.99mb User : Riadh
[matlab] NAPSAC.m DL : 0: RANSAC image registration software
Date : Size : 1kb User : Aeolos
[AI-NN-PR] PCNN DL : 0: 利用改进的脉冲神经网络完成灰度图像的分割-The use of impulsive neural networks to improve the completion of gray-scale image segmentation
Date : Size : 1kb User : 岳碧波
[matlab] ruihua DL : 0: matlab图像增强包括直方均衡，平滑，锐化，具体实现源代码-matlab image enhancement, including straight side balanced, smooth, sharpen, the specific implementation source code
Date : Size : 3kb User : 英子
[Compress-Decompress algrithms] SIFT DL : 0: 在Matlab中实现基于旋转尺度不变特征提取特征点的方法。-Matlab implementation of the rotation based on scale-invariant feature extraction method of feature points.
Date : Size : 2.51mb User : quanshuiwusheng
[Compress-Decompress algrithms] COMPRESSION_NN DL : 0: this the code for image compression using neural network.-this is the code for image compression using neural network.
Date : Size : 1.25mb User : satya
[matlab] otsu DL : 0: OTSU Gray-level image segmentation using Otsu s method. Iseg = OTSU(I,n) computes a segmented image (Iseg) containing n classes by means of Otsu s n-thresholding method (Otsu N, A Threshold Selection Method from Gray-Level Histograms, IEEE Trans. Syst. Man Cybern. 9:62-66 1979). Thresholds are computed to maximize a separability criterion of the resultant classes in gray levels. OTSU(I) is equivalent to OTSU(I,2). By default, n=2 and the corresponding Iseg is therefore a binary image. The pixel values for Iseg are [0 1] if n=2, [0 0.5 1] if n=3, [0 0.333 0.666 1] if n=4, ... [Iseg,sep] = OTSU(I,n) returns the value (sep) of the separability criterion within the range [0 1]. Zero is obtained only with images having less than n gray level, whereas one (optimal value) is obtained only with n-valued images.- OTSU Gray-level image segmentation using Otsu s method. Iseg = OTSU(I,n) computes a segmented image (Iseg) containing n classes by means of Otsu s n-thresholding method (Otsu N, A Threshold Selection Method from Gray-Level Histograms, IEEE Trans. Syst. Man Cybern. 9:62-66 1979). Thresholds are computed to maximize a separability criterion of the resultant classes in gray levels. OTSU(I) is equivalent to OTSU(I,2). By default, n=2 and the corresponding Iseg is therefore a binary image. The pixel values for Iseg are [0 1] if n=2, [0 0.5 1] if n=3, [0 0.333 0.666 1] if n=4, ... [Iseg,sep] = OTSU(I,n) returns the value (sep) of the separability criterion within the range [0 1]. Zero is obtained only with images having less than n gray level, whereas one (optimal value) is obtained only with n-valued images.
Date : Size : 2kb User : ltrko9kd
[Algorithm] fisherprotected DL : 0: fisherface based image retrival
Date : Size : 301kb User : sudarshan
[matlab] imagecycle DL : 0: matlab中图像的循环读入程序，我做了图像imadd叠加操作，别的函数也可以类似的使用这种循环-matlab image read into the program cycle, I make an image overlay imadd operations, other functions can also be similar to the use of this Cycle
Date : Size : 14kb User : 雨田
[Compress-Decompress algrithms] SPIHT-dwt-bandelet DL : 1: 基于wavelet和bandelet的spiht图像压缩！-And wavelet-based image compression spiht the bandelet!
Date : Size : 497kb User : bird
[matlab] travailenmat DL : 0: matlab programming for clustering pam , k-means , dbscan , optics for image segmentation
Date : Size : 21kb User : Ben hassen Amer
[matlab] legend11_a DL : 0: matlab - image processing - averaging filter-matlab- image processing- averaging filter
Date : Size : 49kb User : legend11
[matlab] legend11_m DL : 0: matlab - image processing - median filter-matlab- image processing- median filter
Date : Size : 204kb User : legend11
[matlab] legend11_l DL : 0: matlab - image processing - laplacian filter-matlab- image processing- laplacian filter
Date : Size : 53kb User : legend11

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