A single plant segmentation method of maize point cloud based on Euclidean clustering and K-means clustering

Abstract

Listen

Translate article

It is very important to study the correlation between phenotypic information and genetic information of population maize plants for breeding good maize varieties. How to separate single maize plants from population plants to more accurately measure maize phenotypic parameters is still a difficult problem. Therefore, we propose a single plant segmentation method based on Euclidean clustering and K-means clustering. First, three dimensional (3D) point cloud data of two planting density populations of maize (field 1 and field 2) at five-leaf stage (V5) and six-leaf stage (V6) were obtained by terrestrial laser scanning (TLS). Second, the point cloud data of maize plants were preprocessed to extract the point cloud data of the experimental area. Then, plane segmentation, point cloud filtering and Euclidean clustering were used to segment the population maize plants. Finally, the number of plants and center point of point cloud of maize plants after preliminary segmentation were obtained by voxel filtering, and then K-means clustering was used to achieve single segmentation of maize plants. When planting density was sparse, the segmentation results based on Euclidean clustering and K-means clustering showed that the Accuracy* F1 Score (A * F1) of V5 stage and V6 stage plants were 100.00 % and 99.87 %, respectively; and the A * F1 of V5 stage and V6 stage were 99.59 % and 85.69 %, respectively, when planting density was dense. Compared with the results of Euclidean clustering single plant segmentation, maize single plant segmentation A * F1 increased by 0.00 %, 6.02 %, 12.25 % and 73.41 % at V5 stage and V6 stage in field 1 and field 2, respectively. The results showed that the single plant segmentation based on Euclidean clustering and K-means clustering method could solve the problem that Euclidean clustering single plant segmentation method could not segment the cross-leaf plants. This study provides a simple and reliable method for plant segmentation of population maize for breeders and crop phenotypists.