Liyong Qi

Papers

Total Citations

H-Index

About

Liyong Qi is a pioneering researcher in agricultural robotics, with a focused expertise in computer vision and image processing for greenhouse harvesting automation. His work centers on developing robust algorithms for cucumber identification and localization, a critical challenge for autonomous harvesting robots in complex natural environments. Qi’s most influential contribution is the "Multi-template matching algorithm for cucumber recognition in natural environment" (2016), which has garnered 47 citations and represents a significant leap in enabling robots to detect cucumbers amidst foliage and variable lighting. Earlier foundational work includes a dynamic threshold segmentation algorithm (2009) that optimized cucumber image segmentation using the M (M=2G) color component for improved accuracy, and a novel approach applying rough set theory to cucumber image segmentation (2007), which combined color channels and branch-quantity analysis to enhance target identification. Though his citation counts are modest, Qi’s incremental innovations directly address the practical hurdles of real-world agricultural robotics, laying essential groundwork for future harvesting systems. His research remains highly relevant for students and engineers working on vision-guided agricultural robots.