Location and Recognition Fruit Trees Based on Binocular Stereo Vision

Abstract : In order to improve pesticide utilization rate and reduce the environmental pollution caused by pesticide ground loss, this paper proposes to use binocular vision to recognize the contour and distance information of fruit trees. To improve the recognition accuracy and speed, focusing on the optimization of SIFT stereo matching algorithm. A method for matching the feature points of left and right images base on cosine distance and the vector modulus is proposed. On this basis, two stereo matching algorithms are compared, The accuracy of the Improved SIFT stereo matching algorithm is improved by 1.53%, With this method, the recognition time is almost unchanged, And the stability of depth measurement is analyzed. When the target distance sensor is 180 cm–220 cm, the standard deviation is 1.3592 cm, can meet the requirements of the work.
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Xueguan Zhao, Yuanyuan Gao, Songlin Wang, Xiu Wang, Pengfei Fan, et al.. Location and Recognition Fruit Trees Based on Binocular Stereo Vision. 11th International Conference on Computer and Computing Technologies in Agriculture (CCTA), Aug 2017, Jilin, China. pp.460-472, ⟨10.1007/978-3-030-06179-1_46⟩. ⟨hal-02111527⟩

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