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这是我们的数字图像处理的大作业，用模糊聚类的方法做的图像分割，希望对大家有用，谢谢！-This is our large digital image processing operations, with the fuzzy clustering method to do image segmentation, hope for all of us, thank you!
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边缘检测1.制作一张包括色块、线条的单色背景图片，先对其作低通滤波产生一幅色块和线条边缘模糊的降质图片待处理，采用任意二种边缘检测算法检测待处理图片中的色块和线条的边缘，得到二值化的处理结果图。从结果图中提取色块和线条的边界坐标值，与实际生成原始图像时采用的真实坐标数据作比较，对产生的检测误差作分析。2.拍摄一张包含待检测物体的黑白或者彩色照片，试采用一种边缘检测的算法做待检测物体的自动提取，对生成的结果作分析。-Edge Detection 1. To produce a including
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用matlab生成下列500*500的RGB红绿蓝彩色图像，框内的颜色如图所示（a）假定将该图像转换到HSI空间，用25*25的平均模板模糊H分量图像，再转换回RGB空间，会看到什么结果?-Generated with matlab the following 500* 500 RGB red, green and blue color image, the color box as shown (a) assumes that the image is converted to HSI spa
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使用模糊方法提取的颜色直方图，得到图像的HSV空间的H,S,V值-Extracted using the fuzzy color histogram, the image of the HSV space by H, S, V values
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基于matlab的模糊均值C的聚类程序，可以实现彩色图像的聚类，能实现程序时间统计-Matlab-based fuzzy mean C clustering procedures, can achieve color image clustering, to achieve the program time statistics
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In this post, we are going to share with you, the MATLAB implementation of Color Quantization and Color Reduction of images, using intelligent clustering approaches: (a) k-Means Algorithm, (b) Fuzzy c-Means Clustering (FCM), and (c) Self-Organizing M
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Color Reduction and Quantization using k-Means, Fuzzy Clustering (FCM), and SOM Neuarl Network in MATLAB
In this post, we are going to share with you, the MATLAB implementation of Color Quantization and Color Reduction of images, using intelligent c
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