首页> 外文会议>Education Technology and Computer Science, 2009. ETCS '09 >A Hybrid Method of Block-Based Region Growing and Visible Color Difference for Color Image Segmentation
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A Hybrid Method of Block-Based Region Growing and Visible Color Difference for Color Image Segmentation

机译:基于块的区域增长和可见色差的混合方法用于彩色图像分割

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In this paper we propose a color image segmentation algorithm based on visible color difference and block-based region growing techniques. Firstly, the original image is divide into image blocks which are not overlapped; then, the mean and variance of each image black was calculated in CIEL*a*b* color space, and the image blocks were divided into homogeneous color blocks and texture blocks by the variance of it. The Initial seed regions are automatically selected depending on calculating the homogeneous color blockspsila color difference in CIEL*a*b* color space and spatial and adjacent information. The quadtree decomposition algorithm was applied to split and merge the texture blocks. Finally, the region growing and merging algorithm was to use and achieve the segmentation result. The experimental segmentation results hold favorable consistency in terms of human perception, and confirm effectiveness of the algorithm.
机译:在本文中,我们提出了一种基于可见色差和基于块的区域增长技术的彩色图像分割算法。首先,将原始图像划分为不重叠的图像块;然后,在CIEL * a * b *颜色空间中计算每个图像黑色的均值和方差,并通过其方差将图像块分为同质颜色块和纹理块。根据计算CIEL * a * b *颜色空间中的同质色块psila色差以及空间和相邻信息,自动选择初始种子区域。四叉树分解算法用于分割和合并纹理块。最终,区域增长与融合算法得以使用并获得分割结果。实验分割结果在人类感知方面保持了良好的一致性,并证实了该算法的有效性。

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