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Communication Dans Un Congrès Année : 2013

Automatic Detection of Kiwifruit Defects Based on Near-Infrared Light Source

Pingping Li
  • Fonction : Auteur
  • PersonId : 986507
Yongjie Cui
  • Fonction : Auteur
  • PersonId : 986508
Yufeng Tian
  • Fonction : Auteur
  • PersonId : 986509
Fanian Zhang
  • Fonction : Auteur
  • PersonId : 986510
Xiaxia Wang
  • Fonction : Auteur
  • PersonId : 986511
Shuai Su
  • Fonction : Auteur
  • PersonId : 986512

Résumé

A mathematical model that expresses the relationship between Near-infrared light intensity and automatic threshold for automatic kiwifruit surface defect detection was established. By applying different levels of Near-infrared light intensity to machine vision system, 268 images were collected. Then the images were processed with MATLAB using the method to detect kiwifruit defects based on Near-infrared light source .The obtained 268 sets of data on Automatic Threshold T0 and Manual Threshold T1were divided into 19 groups according to different aperture and light intensity. After processing data, a series of linear equations about the relationship between Near-infrared light intensity and Automatic Threshold T0, with function fitting coefficient of R2 > 95% was obtained. Finally, relationship between T0 and T1 was analyzed according to the effectiveness of image processing results and constant P was introduced to revise Automatic Threshold T0.Thus, a mathematical model needed to gain kiwifruit defects detection threshold, namely Model Threshold T, was established.
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hal-01348099 , version 1 (22-07-2016)

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Pingping Li, Yongjie Cui, Yufeng Tian, Fanian Zhang, Xiaxia Wang, et al.. Automatic Detection of Kiwifruit Defects Based on Near-Infrared Light Source. 6th Computer and Computing Technologies in Agriculture (CCTA), Oct 2012, Zhangjiajie, China. pp.189-198, ⟨10.1007/978-3-642-36124-1_24⟩. ⟨hal-01348099⟩
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