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: 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! Platform: |
Size: 209920 |
Author:郑强 |
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Description: 文中的方法是把图像分块，小波分解得到低频分量、高频分量，然后计算每一块的对比度，把图像块划分为清晰块、模糊块，把清晰块和模糊块相邻的区域定义为边界区域，融合时，直接选取清晰块作为融合后的相应块，对于边界区域，在小波分解的基础上采用基于对比度的像素选取的方法进行处理。-Paper, the method is to image segmentation, wavelet decomposition are low frequency, high frequency components, then calculate the contrast of each piece, the image block is divided into clear blocks, fuzzy block, to clear blocks and fuzzy block is defined as the border region adjacent to area, integration time, a clear block directly select the corresponding block as a fusion, for the border region, the wavelet decomposition on the basis of the pixel-based contrast method selected for processing. Platform: |
Size: 338944 |
Author:许国柱 |
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Description: c#编写的模糊C均值算法处理图像分割，可以处理彩色图像，一个不错的程序-c# write processing fuzzy C means algorithm image segmentation, can handle color images, a good program Platform: |
Size: 89088 |
Author:吴尘秋 |
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Description: 非常好用的基于区域信心的图像分割程序，可以对边缘信息模糊的图像进行处理。IVC-Based on region is very nice confidence image segmentation procedure, can be on the fringe of the fuzzy information using image processing.
Platform: |
Size: 259072 |
Author:孟尚 |
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Description: 一个新的图像识别和解释系统模糊的图像,本文提出。一些重要的规则复杂的时刻提出了模糊的形象和校对。该系统是由区域分割、图像识别和图像解释过程。作为预处理的区域分割过程中,一个输入图像分为一些适当的地区使用基于attention-driven技术方法。 模糊推理神经网络是受雇于上述两幅图像识别和这个解释过程。下图表的模糊效果给出了。实验表明,提出的系统可以被成功地用于识别模糊化的图像。- A new image recognition and interpretation system for
the blurred image is proposed in this paper. Some important
rules of complex moments for the blurred image are presented
and proofed. The proposed system is composed of regional
segmentation, image recognition and image interpretation
process. As a pre-processing in the regional segmentation process,
an input image is divided into some proper regions using
techniques based on attention-driven approach. Fuzzy inference
neural networks are employed in both the image recognition and
the interpretation processes. The graphs under the blurring effect
are presented. The experiment has shown that the proposed
system can be successfully used in recognition of the blurred
image Platform: |
Size: 314368 |
Author:liuzhao |
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Description: FTH is a fuzzy thresholding method for image segmentation. The method is based on relating each pixel in the image to the different regions via a membership function, rather than through hard decisions. The membership function of each of the regions is derived a fuzzy c-means centroid search. As a consequence, each pixel will belong to different regions with a different level of membership. This feature is exploited through spatial processing to make the thresholding robust to noisy environments. -FTH is a fuzzy thresholding method for image segmentation. The method is based on relating each pixel in the image to the different regions via a membership function, rather than through hard decisions. The membership function of each of the regions is derived a fuzzy c-means centroid search. As a consequence, each pixel will belong to different regions with a different level of membership. This feature is exploited through spatial processing to make the thresholding robust to noisy environments. Platform: |
Size: 15360 |
Author:v.r.s.mani |
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Description: 课程的目的学习了解BMP的图像的结构，学会对BMP图像进行各种处理，图像平滑是指用于突出图像的宽大区域、低频成分、主干部分或抑制图像噪声和干扰高频成分，使图像亮度平缓渐变，减小突变梯度，改善图像质量的图像处理方法。数字图像处理中图像锐化同样是一个重要的部分，其目的有两个：一是使灰度反差增强，增强图像的边缘，使模糊的图像变得清晰起来；这种模糊不是由于错误操作，就是特殊图像获取方法的固有影响。二是提取目标物体的边界，对图像进行分割，便于目标区域的识别等。通过图像的锐化，使得图像的质量有所改变，产生更适合人观察和识别的图像。-Course learning to understand the purpose of the structure of BMP image, learn to various processing of BMP image, the image smooth refers to the large area is used to highlight the image, the low frequency component, trunk or suppress image noise and interference of high frequency components, make the image brightness flat gradient, gradient decrease mutations, improve image quality of the image processing methods. Digital image processing, image sharpening, is also an important part of its purpose has two: one is to make the gray contrast enhancement, enhance image edges, makes fuzzy image become clear This fuzzy is not due to wrong operation, it is the inherent influence of special image acquisition method. 2 it is to extract the boundary of the target object, the image segmentation, to facilitate the identification of the target area and so on. Through image sharpening, makes the quality of the image change, to create more suitable for human observation and identification of the i Platform: |
Size: 2446336 |
Author:chen |
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Description: Fuzzy c-means (FCM) clustering has been widely used in image segmentation. However, in spite of its computational efficiency and wide-spread prevalence, the FCM algorithm does not take the spatial information of pixels into consideration, and hence may result in low robustness to noise and less accurate segmentation. In this paper, we propose the weighted image patch-based FCM (WIPFCM) algorithm for image segmentation.(In this algorithm, we use image patches to replace pixels in the fuzzy clustering,
and construct a weighting scheme to able the pixels in each image patch to have anisotropic weights.thus, the proposed algorithm incorporates local spatial information embedded in the image into the segmentation process, and hence improve its robustness to noise. We compared the novel algorithm
to several state-of-the-art segmentation approaches in synthetic images and clinical brain MR studies.Our results show that the proposed WIPFCM algorithm can effectively overcome the impact of noise and substantially improve the accuracy of image segmentations.) Platform: |
Size: 1437696 |
Author:133549
|
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Description: 多种图像分割方法比较，包括roberts,sobel,prewitt,canny,log,fuzzy等多种经典方式，对同一张图像的处理的不同效果比较，根据需要选择不同的处理算子(Comparison of a variety of image segmentation, including roberts, sobel, prewitt, canny, log, fuzzy, and other classic method of image processing with a comparison of different effects, according to the needs of different processing operator) Platform: |
Size: 1024 |
Author:csm |
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Search - fuzzy image processing segmentation