Description: 模糊聚类分割纹理速度快分割效果很好是常用的分割方法-Fuzzy Clustering Segmentation fast texture segmentation is a good division of commonly used methods Platform: |
Size: 90112 |
Author:li |
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Description: 基于二维直方图的图像模糊聚类分割方法，内有算法的参考论文。-Two-dimensional histogram based on fuzzy clustering image segmentation algorithm, which algorithm has the reference papers. Platform: |
Size: 212992 |
Author:方方 |
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Description: 为进一步进行纹理特征分析，从纹理的方向性人手，给出了纹理方向的数学定义式，合理选择差异函数，
构造了具有物理意义的纹理方向描述特征向量．数据处理方面，运用模糊贴近度的概念，结合改进后的属性均值聚
类算法，对一类具有方向性的纹理图象进行分类与分割实验，取得了较好的结果．试验表明，该方法对纹理的方向
性有很好的描述能力．
关键词 图象分割 纹理方向 纹理分割 神经网络 模糊聚类
-Texture features for further analysis, staff from the texture direction, given the direction of the mathematical definition of texture type, a reasonable choice of the difference function, structure with a physical meaning to describe the direction of the texture feature vector. Data processing, the use of the concept of fuzzy nearness degree, combined with improved properties means clustering algorithm for a class of directional texture image classification and segmentation experiments, achieved good results. Tests show that the method of directional texture has a good description of the capacity. Keywords Image segmentation, texture segmentation texture direction fuzzy clustering neural network Platform: |
Size: 291840 |
Author:wgn |
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Description: 一种基于模糊c均值聚类的彩色图像区域分割方法，该方法首先选用适合的彩色空间，然后利用c均值聚类的方法，最终实现图像分割-Based on fuzzy c-means clustering for color image region segmentation method that first of all choose a suitable color space, and then use c-means clustering approach, the eventual realization of image segmentation Platform: |
Size: 164864 |
Author:xiaogang |
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Description: 利用java编写的模糊C均值聚类算法，可以用来图像无监督聚类及图像分割等。-Using java prepared Fuzzy C-means clustering algorithm, can be used to image non-supervised clustering and image segmentation and so on. Platform: |
Size: 4096 |
Author:huangyu |
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Description: 利用java写的快速模糊C均值算法，用与图像分割，聚类等领域。-Using java to write fast fuzzy C-means algorithm using image segmentation, clustering and other fields. Platform: |
Size: 3072 |
Author:huangyu |
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Description: 关于阈值分割的多种算法及其应用。其中有多阈值分割法，自适应模糊阈值分割 及其一些在红外图片上的应用-Threshold segmentation on a variety of algorithms and their applications. One more threshold segmentation method, adaptive fuzzy threshold segmentation and some in the infrared image on the Application of Platform: |
Size: 5532672 |
Author:刘 |
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Description: 基于小波和模糊理论的纹理分割方法,过程非常详细-Based on wavelet theory and fuzzy texture segmentation method, a very detailed process Platform: |
Size: 286720 |
Author:机机 |
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Description: Semantic analysis of multimedia content is an on going research
area that has gained a lot of attention over the last few years.
Additionally, machine learning techniques are widely used for multimedia
analysis with great success. This work presents a combined approach
to semantic adaptation of neural network classifiers in multimedia framework.
It is based on a fuzzy reasoning engine which is able to evaluate
the outputs and the confidence levels of the neural network classifier, using
a knowledge base. Improved image segmentation results are obtained,
which are used for adaptation of the network classifier, further increasing
its ability to provide accurate classification of the specific content. Platform: |
Size: 831488 |
Author:焦亚民 |
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Description: FCM 模糊C均值聚类算法。使用说明：这是一个可以人机交互的FCM算法，首先使用鼠标圈定一个矩形区域，则算法自动施加于目标区域:) Have Fun :)-FCM fuzzy C means clustering algorithm. Usage: This is a can of HCI FCM algorithm, the first to use the mouse a rectangular area delineation, the algorithm automatically imposed on the target area:) Have Fun:) Platform: |
Size: 132096 |
Author:zxr |
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Description: 模糊均值聚类FCM算法对图像的颜色聚类 进行图像分割 聚类个数和聚类中心都是事先决定的-Fuzzy-means clustering algorithm FCM clustering for color image segmentation and clustering the number of cluster centers are determined in advance Platform: |
Size: 515072 |
Author:小五子 |
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Description: 模糊均值聚类FCM 对图像颜色进行聚类 然后对图像进行分割 -Fuzzy-means clustering FCM clustering of the images and then color image segmentation Platform: |
Size: 152576 |
Author:小五子 |
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Description: Image thresholding has played an important role in image segmentation. In this paper, we present a novel spatially weighted fuzzy c-means (SWFCM) clustering algorithm for image thresholding. The algorithm is formulated by incorporating the spatial neighborhood information into the standard FCM clustering algorithm. Two improved implementations of the k-nearest neighbor (k-NN) algorithm are introduced for calculating the weight in the SWFCM algorithm so as to improve the performance of image thresholding. Platform: |
Size: 293888 |
Author:silviudog |
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Search - fuzzy segmentation