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Adopt adaptive B-spline to embellish contours in image segmentation

机译:采用自适应B样条曲线以在图像分割中的装饰轮廓

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摘要

Image segmentation is an important process in computer vision. Most of the currently popular methods tracking the object edge depend on pixel gray value. Because of the noise in images the pixel resoling and the precision of the detection method itself, the detected contours are far from smoothness and with many tiny zigzags which will affect the subsequent processing such as image recognition, image feature detection et al. This paper post forwards a novel method to get smooth contour in image segmentation process. Firstly, adopt dynamic programming algorithm to process the object image and to get a global optimal boundary, then smoothing and fitting the boundary by adaptive B-Spine, which adjusts the control points depending an the contour curvature. Practical numerical experimental results show that this method has stronger edge detection ability and produced smoother contour carve than other methods and without losing edge feature at the same time.
机译:图像分割是计算机愿景中的一个重要过程。跟踪对象边缘的大多数当前流行的方法取决于像素灰度值。由于图像中的噪声是像素解析和检测方法本身的精度,所检测的轮廓远远远非光滑度,并且具有许多微小的曲折,这将影响随后的图像识别等处理,图像特征检测等。本文发布了一种新颖的方法来获得图像分割过程中的平滑轮廓。首先,采用动态编程算法来处理对象图像并获得全局最佳边界,然后通过自适应B脊柱平滑并拟合边界,这根据轮廓曲率调整控制点。实际数值实验结果表明,该方法具有较强的边缘检测能力,并产生比其他方法的更平滑的轮廓,并且同时不失边缘特征。

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