Mihai Bulea

Papers

Total Citations

H-Index

About

Mihai Bulea’s research focuses on computer vision and geometric shape recognition, with particular emphasis on adaptive algorithms for robotic perception and industrial quality control. His most cited work, “Adaptive recognition method for 2D polygonal objects” (2011), introduces a novel approach for detecting and recognizing convex polygonal shapes in digital images. The method employs an adaptive vertex detection technique combined with polygonal fitting, making it especially suitable for real-time applications in robot vision, automated inspection, and photogrammetry. Although his citation count is modest, Bulea’s contribution addresses a practical challenge in machine vision: robustly identifying geometric objects under varying conditions. His algorithm’s adaptability to different convex shapes demonstrates a thoughtful balance between computational efficiency and recognition accuracy. This work has been cited in subsequent studies on shape analysis and industrial automation, reflecting its utility in applied computer vision. Bulea’s research represents a focused effort to bridge theoretical geometry with practical engineering solutions, offering a clear, implementable method for systems that require reliable object recognition in constrained environments.