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image segmentation using k-means partitional clustering algorithm, matlab code
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The K-means algorithm has been widely used in the segmentation of color images for many applications, such as color blood corpuscle accounting, natural image segmentation, face detection of fruit accounting, detection of oil overflow, and biology mic
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基于K-means聚类算法对彩色图象进行分割,聚类的个数可由自己定义.-Based on K- means clustering algorithm for color image segmentation,and the number of clustering can be defined by yourself.
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image segmentation with k-means
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rgb转化为lab空间,k-means聚类,基本的图像处理如腐蚀膨胀等,分水岭分割方法分割标记-rgb converted to lab space, k-means clustering, basic image processing such as corrosion expansion, etc., watershed segmentation segmentation mark
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基于人类视觉将图像分割成若干个有意义的区域是目标检测和模式识别的基础。图像分割属于图像处理中一种重要的图像分析技术。图像分割的基本方法是对灰度图像分割,处理图像的亮度分量,简单快速。本论文介绍了传统的图像分割与K-均值聚类算法分割,然后利用OpenCV函数将其实现,并介绍了OpenCV中图像分割相关的基本函数。-Based on the human visual image is segmented into several meaningful regions is the basis for
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在图像分割中所涉及到的k均值聚类,这个方程fuction:[IDX P] = kmeans(V, k),要求输入样本以及聚类数目,得到聚类值以及数目。-In the image segmentation involved in k-means clustering, this equation fuction: [IDX P] = kmeans (V, k), requires the input samples and the number of clusters to give value
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根据图像的颜色对图像进行分割,里面有多个方法,一种是RGB色彩分割,一种是K均值聚类,还有对视频处理分割,有多个测试图-According to the color image on the image segmentation, there are multiple ways, one is RGB color segmentation, one is the K-means clustering, and video processing division, a plurality of t
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实现图像的Kmeans聚类,完美实现图像分割-The K Means clustering of image, the perfect image segmentation
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运用k-means算法对图像进行分割处理。-Using k-means algorithm for image segmentation process.
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Adaptive K means algorithm for medical image segmentation , It is very useful for ultrasound images-Adaptive K means algorithm for medical image segmentation , It is very useful for ultrasound images
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纹理图像的分割,使用k-means分割,代码主要介绍了特征的提取,具体的参数设定-Texture image segmentation, the use of k-means segmentation, the code describes the feature extraction, the specific parameter settings
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利用libsvm进行图像分割,其结果比k-means以及fcm都要好一点-libsvm to image segmentation
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用K-MEANS算法进行图像的分割,并且有详细的语句注释-With K- MEANS algorithm for image segmentation, and a detailed statement annotations
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基于K-means的优化聚类中心的图像分割算法,改进了FCM算法的缺点-Based on the optimization of K-means clustering center image segmentation algorithm to improve the shortcomings of the FCM algorithm
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中介真值程度度量,基于中介真值程度度量的图像分割本程序的性能已经超过其他算法,基于K均值的PSO聚类算法。- The true extent of the value of the intermediary measure, measure the true extent of the agency based on the value of image segmentation This program has exceeded the performance of other algorit
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聚类算法,遥感影像分割,包含k means,isodata,模糊c聚类,模糊阈值聚类(clustering algorithm,image segmentation,K means,isodata)
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该方法采用gabor提取出图像纹理特征,最后采用k-means方法聚类进行图像分割(The method uses gabor texture features extraction, and finally using k-means clustering methods for image segmentation)
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使用k-means聚类实现多光谱图像分割,并配有高维视图查看聚类结果(Clustering algorithm for multispectral image segmentation)
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We will demonstrate a raster image segmentation process by developing a code in C# that implements k-means clustering algorithm adaptation to perform an image segmentation.
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