Integrating Fuzzy Logic and Morphological Edge Detection for Enhanced UAV Orthomosaic Mapping

The field of engineering is undergoing continuous advancements aimed at optimizing efficiency and precision. Surveying and mapping, fundamental components of Geomatics engineering, have evolved significantly with the adoption of advanced technologies. Among these, ‘Unmanned Aerial Vehicles (UAVs)’ have been a spotlighted tool for conducting precise and efficient surveying and mapping. This study leverages UAV-acquired data to generate high-resolution point clouds and three-dimensional textured mesh models, forming the basis for Orthomosaic imagery creation. The research highlights critical challenges encountered during the generation and analysis of Orthomosaic images, emphasizing the need for image correction and enhancement to achieve application-level precision in accurate mapping and monitoring. To address these challenges, the study integrates Fuzzy Logic and advanced Edge Detection techniques in image processing to enhance the quality and accuracy of Orthomosaic imagery. The findings provide valuable insights into the methodologies and outcomes of the proposed approach, demonstrating its potential to significantly improve the precision and efficiency of Orthomosaic applications. Furthermore, this research underscores the broader implications for engineering and environmental studies, paving the way for more effective and innovative solutions in these domains.