Traditional wolfberry sorting primarily uses artificial method. It has time-consuming and inefficient shortcomings. An automatic wolfberry classification method based on machine vision is proposed. This paper uses digital image processing technology for wolfberry image pre-processing, segmentation and extraction of characteristic parameters of color, size and shape it uses the K-means clustering feature to get the baseline of wolfberry appropriate level it grades wolfberry by minimum distance classifier based on the trained benchmark. The experimental results show that this method can classify different colors and sizes of wolfberry more accurately and quickly.

基于机器视觉的枸杞分级方法.pdf

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