Extraction and Optimization of Microscopic Image Vein Network Based on eCognition Software

Abstract:

The extraction of leaf network and the measurement of its trait parameters provide an important reference for the study of leaf vein ecology. Taking the leaves of six tree species (Sophora japonica, Populus tomentosa, Ailanthus altissima, Fraxinus pennsylvanica, Acer truncutum and Koelreuteria paniculata) with different leaf characteristics as object, the multiscale segmentation of the vein microscopy image was based on eCognition software. Firstly, the microscopic images were segmented. And then the spectral information and object geometry information of microscopic images objects were comprehensively applied to build the road extraction knowledge base. Thirdly, the results of vein extraction were improved and completed in order to increase the integrity of the vein network. The results showed that the optimal thresholds for leaf vein extraction were: scale parameter was 200, shape parameter was 0.7, tightness parameter was 0.3, brightness characteristics value was 230~280, spectral characteristic value was 180~230, geometric feature value was greater than 1.5. The extraction of leaf vein density measurement was more than 93%, which had high universality.