CAJ | 학술논문

针对目前传统的枸杞分级主要采用人工方法，费时费力且效率不高的缺点，提出了一种基于机器视觉技术对枸杞进行自动分类的方法。采用数字图像处理技术对枸杞图像进行了预处理、分割，从而提取枸杞的色泽、大小及形状等特征参数；用K-means算法对特征进行聚类，得到枸杞相应等级的基准；根据聚类分析得到的基准采用最小距离分类器对枸杞进行分级。实验结果表明，该方法能够准确快速地对不同色泽和大小的枸杞进行分类。
침대목전전통적구기분급주요채용인공방법，비시비력차효솔불고적결점，제출료일충기우궤기시각기술대구기진행자동분류적방법。채용수자도상처리기술대구기도상진행료예처리、분할，종이제취구기적색택、대소급형상등특정삼수；용K-means산법대특정진행취류，득도구기상응등급적기준；근거취류분석득도적기준채용최소거리분류기대구기진행분급。실험결과표명，해방법능구준학쾌속지대불동색택화대소적구기진행분류。
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 tech-nology 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.