地面树木的最优标记分水岭图像分割算法
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1.沈阳理工大学自动化与电气工程学院 沈阳 110159;2. 中国科学院沈阳自动化研究所 沈阳 110015

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TP391.4

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国家自然科学基金(61991413)、辽宁省自然科学基金(2019-ZD-0251)项目资助


A watershed segmentation algorithm based on an optimal marker for ground tree
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1. School of Automation and Electrical Engineering, Shenyang Ligong University, Shenyang 110159, China; 2. Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110015,China

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    摘要:

    为解决复杂地物背景下航拍图像树木检测出现的过分割和误分割问题,提出了一种基于最优标记的改进分水岭图像分割方法。该方法先对输入图像非线性灰度变换提高目标与背景的对比度,再根据目标的形状特征对前景和背景区域初步标记,用前景区域的形心代替传统分水岭算法中的距离变换,二次标记前景,最后使用分水岭算法得到分割图像。实验结果表明,该算法分割准确率平均值为92.5%,比现有图像分割方法抗噪性更强、准确率更高,同时改善了分水岭算法过分割问题。

    Abstract:

    In order to solve the over-segmentation and incorrect segmentation in tree detection of aerial image under complex terrain background, a watershed segmentation algorithm based on optimal marker was proposed. In this method, firstly, the contrast between the target and the background is improved by nonlinear gray transformation. Secondly, the foreground and background areas are initial marked according to the shape characteristics of the target, then the distance transformation in the traditional watershed algorithm is replaced by the centroid of the foreground area, and the foreground is marked again. Finally, the image is segmented by the watershed algorithm. The experimental results show that the average segmentation accuracy of this algorithm is 92.5%, which is more anti-noise and accurate than the existing image segmentation methods, and also solves the over-segmentation problem of the watershed algorithm.

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刘 军,张艳迪,高宏伟,于洋.地面树木的最优标记分水岭图像分割算法[J].电子测量技术,2021,44(17):46-53

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  • 在线发布日期: 2024-08-09
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