CAJ | 학술논문

为适应农业采摘机器人对葡萄对象快速准确识别的需要，提出了基于 HSI 色彩空间与以直方图信息为特征的快速模糊C－均值聚类（ FFCM ）算法相结合的葡萄图像分割方法。该方法以 H 分量作为葡萄图像聚类分割的处理数据，根据FFCM 算法对灰度图像聚类分割。试验对夏黑葡萄果实在自然光、顺光、背光照射环境下拍摄的图像进行分割。结果表明：葡萄图像分割方法能够快速且较好地从复杂自然环境中将葡萄目标分割出来，为葡萄采摘机器人的研制提供了重要参考。
위괄응농업채적궤기인대포도대상쾌속준학식별적수요，제출료기우 HSI 색채공간여이직방도신식위특정적쾌속모호C－균치취류（ FFCM ）산법상결합적포도도상분할방법。해방법이 H 분량작위포도도상취류분할적처리수거，근거FFCM 산법대회도도상취류분할。시험대하흑포도과실재자연광、순광、배광조사배경하박섭적도상진행분할。결과표명：포도도상분할방법능구쾌속차교호지종복잡자연배경중장포도목표분할출래，위포도채적궤기인적연제제공료중요삼고。
In order to adapt to the agricultural picking robots needing to recognize grapes quickly and accurately , a new segmentation method that based on HSI color space and fast fuzzy C-means clustering ( FFCM ) algorithm characterized by histogram informations is presented .This method is that original RGB images is transformed into HSI images , and using H component as clustering segmentation of data to cluster gray image according to the FFCM algorithm .By analying the testing of xiahei grapes under natural light , facing of the light and backlight ,the image segmentation method of this paper can split grapes fastly from the complex natural environments and provide some references for the research of agri -cultural robots .