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- W2401225997 abstract "This paper studies bruise detection in apples using 3-D imaging. Bruise detection based on 3-D imaging overcomes many limitations of bruise detection based on 2-D imaging, such as low accuracy, sensitive to light condition, and so on. In this paper, apple bruise detection is divided into two parts: feature extraction and classification. For feature extraction, we use a framework that can directly extract local binary patterns from mesh data. For classification, we studies support vector machine. Bruise detection using 3-D imaging is compared with bruise detection using 2-D imaging. 10-fold cross validation is used to evaluate the performance of the two systems. Experimental results show that bruise detection using 3-D imaging can achieve better classification accuracy than bruise detection based on 2-D imaging." @default.
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- W2401225997 date "2016-05-19" @default.
- W2401225997 modified "2023-09-25" @default.
- W2401225997 title "Fruit bruise detection based on 3D meshes and machine learning technologies" @default.
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- W2401225997 doi "https://doi.org/10.1117/12.2223336" @default.
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