成熟期苹果树冠层器官异源图像配准
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国家自然科学基金资助项目(31371532)和中央高校基本科研业务费专项资金资助项目(2013YJ008)


Multi-source Image Registration for Canopy Organ of Apple Trees in Mature Period
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    摘要:

    精确构建果树冠层彩色三维空间结构,以成熟期苹果树冠层为研究对象,将PMD摄像机及彩色摄像机相结合获取冠层器官异源图像,开展异源信息配准技术研究。将SIFT算法应用于异源图像特征点提取研究中,并应用目标函数优化RANSAC算法完成同名点提纯以保证特征点匹配的有效性,避免了异源图像尺度变化及果园自然光照的影响;在分析异源图像成像效果基础上,确定了应用双线性映射模型求解异源图像空间映射关系,有效克服了应用仿射变换模型求解异源图像空间映射关系的不精确性。果园不同自然环境下的配准实验表明:提出的混合算法适用于苹果树冠层器官异源图像的配准,晴天顺光环境下的正确配准率为88.2%,晴天逆光环境下的正确配准率为84.2%,阴天环境下的正确配准率为72.7%。

    Abstract:

    In order to construct colorful 3-D spatial structure of canopy accurately, apple tree canopies of maturation period were set for research object, and a PMD camera and a color camera were used to acquire multi-source organ images of apple tree canopies, which aimed at studying registration of multi-source images. SIFT algorithm was used to extract characteristic points from multi-source images and RANSAC algorithm optimized by objective function was adopted to purify feature vectors, which overcame scale change and effect of light. Bilinear mapping algorithm was employed as spatial mapping between multi-source images to avoide inaccuracy of using affine transformation to solve space mapping. The registration test in orchards with different natural environment showed that the method proposed was suitable for registration of multi source images of apple tree canopies, and the registration accuracy could be 88.2% in sunny day of light environment, 84.2% in sunny day of backlight environment, 72.7% in cloudy day. The research finding could provide maintenance assurance for picking and yielding links of apple orchard after 3-D reconstruction of canopies.

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马晓丹,刘 刚,冯 娟,周 薇.成熟期苹果树冠层器官异源图像配准[J].农业机械学报,2014,45(4):82-88.

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  • 收稿日期:2013-06-13
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  • 在线发布日期: 2014-04-10
  • 出版日期: 2014-04-10