Journal of Korea Multimedia Society (한국멀티미디어학회논문지)

Korea Multimedia Society (한국멀티미디어학회)
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Automatic Fruit Grading Using Stacking Ensemble Model Based on Visual and Physical Features

시각적 특징과 물리적 특징에 기반한 스태킹 앙상블 모델을 이용한 과일의 자동 선별

  • Kim, Min-Ki (School of Computer Science, Gyeongsang National University, Engineering Research Institute)
  • Received : 2022.08.02
  • Accepted : 2022.10.04
  • Published : 2022.10.31
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Abstract

As consumption of high-quality fruits increases and sales and packaging units become smaller, the demand for automatic fruit grading systems is increasing. Compared to other crops, the quality of fruit is determined by visual characteristics such as shape, color, and scratches, rather than just physical size and weight. Accordingly, this study presents a CNN model that can effectively extract and classify the visual features of fruits and a perceptron that classifies fruits using physical features, and proposes a stacking ensemble model that can effectively combine the classification results of these two neural networks. The experiments with AI Hub public data show that the stacking ensemble model is effective for grading fruits. However, the ensemble model does not always improve the performance of classifying all the fruit grading. So, it is necessary to adapt the model according to the kind of fruit.

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References

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