首页> 外文会议>Proceedings of the International Conference on Imaging Science, Systems, and Technology (CISST'2000) >Fusion of Normalized Color and Rough Set Theoretic Approximations for Robust Color Image Segmentation
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Fusion of Normalized Color and Rough Set Theoretic Approximations for Robust Color Image Segmentation

机译:归一化颜色和粗糙集理论逼近的融合,用于稳健的彩色图像分割

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A robust technique for the segmentation of color images of natural scenes has been presented. The algorithm focuses on the problem of segmentation of images depicting regions with similar but slightly varying colors into homogenous regions, irrespective of scene geometry, by considering normalized color. For this purpose, a concept of formation of an encrustation on the histogram of normalized color coordinates has been developed. The concept is based on Rough Set Theory. The technique presents scalable levels of information details that can be utilized for the analysis. The technique has been verified by applying it to various natural images.
机译:已经提出了一种用于分割自然场景的彩色图像的鲁棒技术。该算法着重于通过考虑归一化颜色将描绘具有相似但略有变化的颜色的区域的图像分割为同质区域的问题,而与场景几何结构无关。为此,已经提出了在归一化的颜色坐标的直方图上形成结壳的概念。该概念基于粗糙集理论。该技术提供了可用于信息分析的可扩展级别的信息详细信息。该技术已通过将其应用于各种自然图像而得到验证。

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