Research progress of traditional image segmentation algorithm in seed testing of crops
Traditional image segmentation algorithm has been widely used in the field of crop seed testing because of its low complexity in time and space.The application of traditional segmentation algorithm in the crop phenotype extraction was studied in this paper.Firstly,the algorithm principles of Otsu,watershed,edge detection,SLIC and concave point analysis algorithm were expounded.For crop seeds with uniform seed coat color and different shapes,the problems in the application of different algorithms and the corresponding solutions were described in the model of'problem-method'.Then the algorithms were integrated into five categories based on threshold,region,edge,cluster and concave point,and the segmentation effect,advantages and disadvantages and application range of the algorithm were compared.Finally,the problems in the application of crop seed image segmentation were analyzed,and the future research directions were prospected from algorithm accuracy improvement and overlapping occlusion processing,in order to provide reference for the research of image segmentation in the process of crop seed testing.
万方数据
维普
