基于改进Harris角点检测的虚拟樱桃叶片重建方法 |
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引用本文: | 杨立伟,赖文聪,刘刚,刘鑫来,张俊宁,吕树盛. 基于改进Harris角点检测的虚拟樱桃叶片重建方法[J]. 农业机械学报, 2022, 53(S1): 213-217,262 |
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作者姓名: | 杨立伟 赖文聪 刘刚 刘鑫来 张俊宁 吕树盛 |
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作者单位: | 中国农业大学;北京信息科技大学;中国农业机械化科学研究院集团有限公司 |
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基金项目: | 山东省自然科学基金项目(ZR2020MC084) |
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摘 要: | 为了分析樱桃树叶片的形态结构,为樱桃树冠层光照分布及樱桃果树整形修剪提供理论基础,提出了一种基于改进Harris角点检测及NURBS曲线的樱桃树叶片重建方法。利用中值滤波法及经典边缘检测算法对获得的原始樱桃树叶片图像进行预处理,得到树叶轮廓。针对传统NUBRS曲线原理重构轮廓时无法构成闭合曲面,特征点之间相互干扰等问题,提出了一种新的算法来重构轮廓。该算法首先将特征点分为左右两部分,分别重建左右两侧轮廓,再将两者连接得到完整的轮廓;其次运用改进的Harris角点检测法提取角点来作为特征点;再次,通过检测窗口中心点灰度与其周围n邻域内其他像素点灰度的相似程度,计算灰度之差来设定一个阈值,并根据该阈值范围提取角点;最后,根据虚拟轮廓构建虚拟叶片。实验结果表明,改进后的算法大大减少了计算量,平均消耗时间由4.61s减少到2.30s。本文方法较真实地重构了樱桃树叶片边缘形状,为樱桃树冠层光照分布计算提供了技术支持。
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关 键 词: | 樱桃叶片 角点检测 轮廓重建 |
收稿时间: | 2022-06-25 |
Virtual Leaf Reconstruction Method Based on Improved Harris Corner Detection |
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Affiliation: | China Agricultural University;Beijing Information Science and Technology University; Chinese Academy of Agricultural Mechanization Sciences Group Co., Ltd. |
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Abstract: | In order to analyze the morphological structure of cherry tree leaves and provide a theoretical basis for the light distribution of cherry tree canopy and the shaping and pruning of cherry fruit trees,a method for reconstructing cherry tree leaves was proposed based on improved Harris corner detection and Nurbs curve. The obtained original cherry tree leaf images were preprocessed by median filtering method and classical edge detection algorithm to obtain leaf contours. An algorithm was proposed to reconstruct the contour, aiming at the problems that a closed surface cannot be formed when the contour was reconstructed by the traditional NUBRS curve principle, and the feature points interfere with each other. The algorithm first divided the feature points into left and right parts, the contours of the left and right sides were reconstructed respectively, and then the two were connected to obtain a complete contour. Secondly, the improved Harris corner detection method was used to extract corner points as feature points. Thirdly, by detecting the degree of similarity between the gray value of the center point of the window and the gray values of other pixels in the surrounding n neighborhood, the difference between the gray values was calculated to set a threshold, and the corner points were extracted according to the threshold range. Finally, a virtual leaf was constructed according to the virtual contour. Experimental analysis showed that the improved algorithm greatly reduced the amount of useless computation, and the average consumption time was reduced from 4.61s to 2.30s. Based on the improved algorithm, the edge shape of cherry tree leaves can be perfectly maintained, which provided technical support for the calculation of light distribution in the cherry tree canopy. |
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Keywords: | cherry leaves corner detection contour reconstruction |
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