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A Method for Segmentation and Recognition of Mature Citrus and Branches-Leaves Based on Regional Features

  • Sa Liu
  • Changhui Yang
  • Youcheng Hu
  • Lin Huang
  • Longye Xiong
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 875)

Abstract

A novel method based on the regional feature of mature citrus is proposed for segmentation and recognition in order to achieve the segmentation and identification of mature citrus and branches-leaves in Harvesting robots. Feature mapping table is used to reduce the dimension of the feature vector. The ROI (region of interest) size of the target object is determined by the size of picking up the working space of the manipulator, the binocular camera field and the citrus. According to the scores, the consistency of the primary ROI is sorted to a greater degree, and the ROI with the largest score is chosen as the optimal area. The experimental results show that the accuracy of recognition is 94% and the time required for single image segmentation is 0.24 s. This method is better than many existing methods.

Keywords

Mature citrus Feature vector SVM segmentation Region of interest 

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Copyright information

© Springer Nature Singapore Pte Ltd. 2018

Authors and Affiliations

  • Sa Liu
    • 1
  • Changhui Yang
    • 1
    • 2
  • Youcheng Hu
    • 1
  • Lin Huang
    • 1
  • Longye Xiong
    • 1
  1. 1.College of Mechanical EngineeringChongqing University of TechnologyChongqingChina
  2. 2.College of Mechanical EngineeringXi’an Jiaotong UniversityXi’anChina

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