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首页> 外文会议>Conference on Color Imaging: Device-Independent Color, Color Hardcopy, and Graphic Arts Ⅵ Jan 23-26, 2001, San Jose, USA >Shading and Highlight Invariant Color Image Segmentation Using the MPC Algorithm
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Shading and Highlight Invariant Color Image Segmentation Using the MPC Algorithm

机译：使用MPC算法的阴影和高光不变彩色图像分割

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摘要

A new color image segmentation algorithm is presented in this paper. This algorithm is invariant to highlights and shading. This is accomplished in two steps. First, the average pixel intensity is removed from each RGB coordinate. This transformation mitigates the effects of highlights. Next, the Mixture of Principal Components algorithm is used to perform the segmentation. The MPC is implicitly invariant to shading due to the inner vector product or vector angle being used as similarity measure. Since the new coordinate system contains negative numbers, it is necessary to modify the MPC algorithm since in its original form it does not distinguish between positive and negative color space coordinates. Results on artificial and real images illustrate the effectiveness of the method. Finally, the use of the total within-cluster variance is investigated as possible criterion for selecting the number of clusters for the new algorithm.
机译：提出了一种新的彩色图像分割算法。该算法对于高光和阴影是不变的。这分两个步骤完成。首先，从每个RGB坐标中删除平均像素强度。这种转换减轻了高光的影响。接下来，使用“主成分混合”算法执行分割。由于内部矢量积或矢量角度用作相似性度量，因此MPC对阴影隐含不变。由于新坐标系包含负数，因此有必要修改MPC算法，因为其原始形式不能区分正色空间坐标和负色空间坐标。人工和真实图像上的结果说明了该方法的有效性。最后，研究使用总集群内方差作为为新算法选择集群数的可能标准。

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