1673-159X

CN 51-1686/N

自然场景下树上桃子生长形态的识别

Recognition Method of Peaches Growth Morphology in Natural Scene

  • 摘要: 为使机械手更准确地抓取桃子,提出一种在自然光照条件下识别树上桃子生长形态的方法。首先在5种颜色空间中利用BP神经网络找出识别率最高、误分率最低的颜色特征组合(H, Cr(YCgCr),Cr(YCbCr), R-G, 2R-G, Cb-Cr),并使用改进的K-means聚类算法实现图像分割;然后利用桃子生长的形态参数(复杂度、延伸率、紧密度等)使用支持向量机分类器进行分类。实验结果表明:对于晴天拍摄的图片,其识别率可达到87.5%;对于阴天拍摄的图片,其识别率可达80.5%。该方法具有一定的实用价值。

     

    Abstract: In order to pick peaches accurately during the tedious process of harvesting, a recognition method of peaches growth morphology in natural scene method is put forward for robot. In five color spaces, such as H, Cr(YCgCr), Cr(YCbCr), R-G, 2R-G and Cb-Cr, a color combination that has the lowest recognition error rate is found out based on BP neural network and the improved K-means clustering algorithm is used to segment image. According to peach morphology features, such as complexity, elongation, eccentricity, etc., the peach growth morphologies are classfied with support vector machine. Experiment results show that the recognition rate of pictures taken in fine day arrives at 87.5%, and the recognition rate of pictures taken in cloudy day reaches to 80.5%. The results show that the proposed method is practical.

     

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