Supplementary files for "WingSegment: A Computer Vision-Based Hybrid Approach for Insect Wing Image Segmentation and 3D Printing"

Abstract

<p>WingSegment combines computer vision and graph theory to segment images of insect wings. The algorithm is supported by a user-friendly graphical interface created using Matlab App-designer. It allows for the identification of cells, junctions, Pterostigma, and venation patterns in insect wings. WingSegment employs region-growing, thinning, and Dijkstra's algorithms for boundary detection, junction identification, and vein path extraction. Additionally, it calculates geometric features such as the area, length, and circularity of cells, as well as the length of veins. The algorithm also generates histograms and box plots to visualize the measured geometric features. By utilizing cell centroids, WingSegment creates a Voronoi pattern on the wing. Furthermore, the detected boundaries can be exported as FreeCAD macro files, facilitating 3D modeling and further analysis. The accuracy and efficiency of WingSegment are validated through comparisons with established software tools and manual measurements, demonstrating its effectiveness. The results exhibit precise wing segmentation and enable in-depth analysis of wing properties. WingSegment contributes to the advancement of knowledge in insect wing morphology and its applications across various fields.</p&gt