CAJ | 학술논문

针对北方典型牧草植物一苜蓿图像，采用多种常用的灰度化方法，并对其中的超绿法和Cr色彩法进行了改进，结合灰度图的特点，选用了单阀值分割和基于欧式距离的聚类分割方法将图像二值化，实现了苜蓿与背景的分离提取。利用大量的图像样本，对图像的分割准确率进行了统计分析和比较研究，得到了常用算法的定量评价和分割效果，得到了针对苜蓿图像的有效分割方法，为进一步实现牧草自动识别提供了依据。
침대북방전형목초식물일목숙도상，채용다충상용적회도화방법，병대기중적초록법화Cr색채법진행료개진，결합회도도적특점，선용료단벌치분할화기우구식거리적취류분할방법장도상이치화，실현료목숙여배경적분리제취。이용대량적도상양본，대도상적분할준학솔진행료통계분석화비교연구，득도료상용산법적정량평개화분할효과，득도료침대목숙도상적유효분할방법，위진일보실현목초자동식별제공료의거。
Aim at the north typical pasture - alfala image, some methods that can color - to - gray image were used to it, and improve the excess green method and Cr color method. Combined with the gray - scale image features, take the single - threshold segmentation and clustering segmentation based on euclidean distance to reach image binarization, accomplish extraction of alfalfa and background. h lot of image sapmles were used to count the segmentation accuracy, the results show quantitative evaluation and segmentation effect of commonly used algorithms, get the effective segment method to Alfalfa image, provide the basis of automatic pasture identification.