IEIE Transactions on Smart Processing and Computing

The Institute of Electronics and Information Engineers (대한전자공학회)
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A Novel Red Apple Detection Algorithm Based on AdaBoost Learning

  • Kim, Donggi (Department of Computer Engineering, Sejong University) ;
  • Choi, Hongchul (Department of Computer Engineering, Sejong University) ;
  • Choi, Jaehoon (Department of Computer Engineering, Sejong University) ;
  • Yoo, Seong Joon (Department of Computer Engineering, Sejong University) ;
  • Han, Dongil (Department of Computer Engineering, Sejong University)
  • Received : 2015.06.20
  • Accepted : 2015.08.24
  • Published : 2015.08.31
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Abstract

This study proposes an algorithm for recognizing apple trees in images and detecting apples to measure the number of apples on the trees. The proposed algorithm explores whether there are apple trees or not based on the number of image block-unit edges, and then it detects apple areas. In order to extract colors appropriate for apple areas, the CIE $L^*a^*b^*$ color space is used. In order to extract apple characteristics strong against illumination changes, modified census transform (MCT) is used. Then, using the AdaBoost learning algorithm, characteristics data on the apples are learned and generated. With the generated data, the detection of apple areas is made. The proposed algorithm has a higher detection rate than existing pixel-based image processing algorithms and minimizes false detection.

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References

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Cited by

  1. Image Segmentation for Fruit Detection and Yield Estimation in Apple Orchards vol.34, pp.6, 2017, https://doi.org/10.1002/rob.21699