Abstract
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 T 0 and Manual Threshold T 1were 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 T 0, with function fitting coefficient of R 2 > 95% was obtained. Finally, relationship between T 0 and T 1 was analyzed according to the effectiveness of image processing results and constant P was introduced to revise Automatic Threshold T 0.Thus, a mathematical model needed to gain kiwifruit defects detection threshold, namely Model Threshold T, was established.
Foundation item: The Project-sponsored by SRF for ROCS, SEM (KS08021101), Project supported by the National Natural Science Foundation of China (61175099), Northwest Agriculture and Forestry University Talent Fund (Z111020902).
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Li, P., Cui, Y., Tian, Y., Zhang, F., Wang, X., Su, S. (2013). Automatic Detection of Kiwifruit Defects Based on Near-Infrared Light Source. In: Li, D., Chen, Y. (eds) Computer and Computing Technologies in Agriculture VI. CCTA 2012. IFIP Advances in Information and Communication Technology, vol 392. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-36124-1_24
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DOI: https://doi.org/10.1007/978-3-642-36124-1_24
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