Computer Vision-Based Analysis and 3D Modeling of Insect Wings

The study of insect wings is vital in biology and engineering, providing insights into evolutionary adaptations and inspiring biomimetic designs. However, the complex geometry and diverse venation patterns make their study challenging, necessitating automated techniques.

This thesis explores computer vision and image processing to develop four software packages for studying insect wings. WingMesh extracts wing geometry and generates meshes using distmesh2d. WingGram, for finite element (FE) modeling in Abaqus, leverages Python scripting and computer vision, offering speed and practicality for intricate structures. Both WingMesh and WingGram include a new method for easily assigning corrugations to FE models using a secondary image. WingSegment segments wing images to extract cell boundaries, vein patterns, junctions, and Pterostigma location, measuring morphological features and generating statistics in various formats. It also produces sketches in FCMacro format compatible with FreeCAD for 3D models. WingAnalogy, for automated asymmetry analysis, uses Particle Swarm Optimization (PSO) and computer vision to extract wing morphometry and compute asymmetry, allowing for division into cell sets for localized asymmetry measurement.

Additionally, this thesis examines the correlation between wing and cell size across 389 wings from various Odonata families. Despite varying wing sizes, cell size remains remarkably consistent, suggesting a potential crack-stopping mechanism.

The developed tools have been validated, demonstrating precision in modeling, morphometry, and asymmetry analysis for diverse insect wings. These user-friendly, scalable, and accurate methods use embedded algorithms and custom codes for consistency and objectivity. This thesis advances computational entomology by providing efficient tools for insect wing analysis, offering new insights into their structural and functional characteristics.

Rechte

Nutzung und Vervielfältigung:


CC BY 4.0

Bitte beachten Sie, dass einzelne Bestandteile der Publikation anderweitigen Lizenz- bzw. urheberrechtlichen Bedingungen unterliegen können.

Zitieren

Zitierform:
Eshghi Sahraei, S., 2024. Computer Vision-Based Analysis and 3D Modeling of Insect Wings.
Zitierform konnte nicht geladen werden.