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基于支持向量聚类的多聚焦图像融合算法.
从无监督机器学习角度提出了一种基于SVC(support vector clustering)的图像融合规则,解决了基于
SVM(support vector machine)的融合规则在处理多聚焦图像融合问题时所引起的区域混叠与非平滑过渡问题,进一步提高了融合图像的质量.-Based on support vector clustering algorithm for multi-focus image fusion. Never oversig
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基础矩阵估计的聚类分析算法，用于对图像进行聚类分析的算法。-Matrix estimation based on cluster analysis algorithms, used for image analysis algorithm for clustering.
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In this project ,we propose a color based segmentation method that uses the c means clustering technique to track tumor objects in magnetic resonance (MR) brain images. The key concept in this color based segmentation algorithm with k means means to
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k-means clustering for image classification
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This paper presents a new human skin color model in
YCbCr color space and its application to human face
detection. Skin colors are modeled by a set of three
Gaussian clusters, each of which is characterized by a
centroid and a covariance matr
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提出一种新的基于图像特征聚类的自嵌入水印算法( CCSW) ，用于图像内容的认证和恢复．-In this paper，we present a novel self-embedded watermarking algorithm based on characteristic clustering ( CCSW) for
image tamper detection and recovery．
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数据挖掘kmeans图像聚类实验报告
用 VC 或 Java 实现 k-means 聚类算法， 分别以迭代次数及分配不再发生变化为算法终止条件，用图片（自己选择）作为数据集，比较运行时间（画出时间与像素点的关系曲线图，因此须用多幅像素个数不同的图片进行实验） 提交实验报告与源代码。 -Data mining to achieve the k-means clustering algorithm the kmeans image clustering experiment report wit
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Bilateral Filtering using Modified Fuzzy Clustering
for Image Denoising
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模式识别中的模糊聚类，采用隐马尔科夫链，考虑了先验概率，进行图像识别。-Pattern recognition, fuzzy clustering, using hidden Markov chain, taking into account a priori probability for image recognition.
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Generalized Spatial Kernel based Fuzzy C-Means
Clustering Algorithm for Image Segmentation
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This code uses MATLAB s Internal Functions and Memory Preallocations to apply a Fast Implementation of kmeans algorithm. This is a efficient code for clustering a gray or Color image or it can be used for clustering a Multidimensional Array.
Com
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K MEAN CLUSTERING FOR IMAGE PROCESSING
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This paper presents an analytical study on different clustering techniques used for image segmentation
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针对目前传统的枸杞分级主要采用人工方法， 费时费力且效率不高的缺点， 提出了一种基于机器视觉技术对枸杞
进行自动分类的方法。 采用数字图像处理技术对枸杞图像进行了预处理、 分割 ， 从而提取枸杞的色泽、 大小及形状等特征
参数； 用 K-means 算法对特征进行聚类， 得到枸杞相应等级的基准； 根据聚类分析得到的基准采用最小距离分类器对枸杞
进行分级。 实验结果表明 ， 该方法能够准确快速地对不同色泽和大小的枸杞进行分类。-Traditional wolfberry sorting
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Image clustering this method is used to image clustering. Image clustering and categorization is a means for high-level descr iption of image content. The goal is to find a mapping of the archive images into classes (clusters) such that the set of cl
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仿真效果非常好，用于图像处理的独立分量分析，基于K均值的PSO聚类算法。- Simulation of the effect is very good, Independent component analysis for image processing, K-means clustering algorithm based on the PSO.
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利用matlab针对图像进行马氏距离计算 ,是小学期课程设计的题目，基于欧几里得距离的聚类分析。- Using matlab to calculate the Mahalanobis distance for the image, Is the topic of the elementary school stage curriculum design, Clustering analysis based on Euclidean distance.
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