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Experimental combination of intensity and stereo edges for improved snake segmentation

机译:强度和立体边缘的实验组合可改善蛇形分割

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In this paper, we present an algorithm to combine edge information from stereo-derived disparity maps with edges from the original intensity/color image to improve the contour detection in images of natural scenes. After computing the disparity map, we generate a so-called “edge-combination image,” which relies on those edges of the original image that are also present in the stereo map. We describe an algorithm to identify corresponding intensity and disparity edges, which are usually not perfectly aligned due to errors in the stereo reconstruction. Our experiments show that the proposed edge-combination approach can significantly improve the segmentation results of an active contour algorithm.
机译:在本文中,我们提出了一种算法,将立体派生的视差图的边缘信息与原始强度/彩色图像的边缘相结合,以改善自然场景图像中的轮廓检测。在计算完视差图之后,我们生成一个所谓的“边缘组合图像”,它依赖于立体图像中也存在的原始图像的那些边缘。我们描述了一种算法,用于识别相应的强度和视差边缘,由于立体声重建中的错误,这些边缘通常不完全对齐。我们的实验表明,提出的边缘组合方法可以显着改善主动轮廓算法的分割结果。

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