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Finding the Texture Features Characterizing the Most Homogeneous Texture Segment in the Image

机译:查找表征图像中最均匀的纹理片段的纹理特征

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We propose an algorithm for finding a set of texture features characterizing the most homogeneous texture area of an input image. The found set of features is intended for extraction of this segment. The algorithm processes any input images in the absence of any preliminary information about the images and, accordingly, without any learning. The essence of the algorithm is as follows. The image is covered with a number of test windows. In each of them, a degree of texture homogeneity is measured. The test window with maximal degree of homogeneity is determined and a representative patch of pixels is detected. The texture features extracted from the detected representative patch is considered as those that best characterize the most homogeneous texture segment. So, the proposed algorithm facilitates solution of the texture segmentation task by providing a segmentation technique with helpful additional information about the analyzed image. A computer program simulating the algorithm has been created. The program is tested on natural grayscale images.
机译:我们提出了一种算法,用于查找表征输入图像最均匀纹理区域的一组纹理特征。找到的特征集旨在提取此段。该算法在不存在有关图像的任何初步信息的情况下处理任何输入图像,因此无需任何学习。该算法的实质如下。该图像覆盖了许多测试窗口。在它们中的每一个中,都测量质地均匀性的程度。确定具有最大均匀度的测试窗口,并检测像素的代表性斑块。从检测到的代表性补丁中提取的纹理特征被认为是最能表征最均匀纹理片段的纹理特征。因此,所提出的算法通过提供具有关于被分析图像的有用的附加信息的分割技术来促进纹理分割任务的解决。已经创建了模拟算法的计算机程序。该程序已在自然灰度图像上进行了测试。

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