Naomi Henderson
Papers
1
Total Citations
11
H-Index
1
About
Naomi Henderson’s research focuses on computer vision and autonomous robotics, with a particular emphasis on colour perception and calibration for mobile systems. Her most cited work, “An automated colour calibration system using multivariate Gaussian mixtures to segment HSI colour space” (2008, 11 citations), addresses a critical bottleneck in robotics: the labor-intensive manual calibration of colour sensors. By converting YUV images to HSI format and applying multivariate Gaussian mixtures to segment distinct colour regions, Henderson developed an automated system that enables robots to adapt to changing lighting conditions without human intervention. This contribution laid groundwork for more robust, real-world deployment of vision-guided robots. While her citation count reflects a niche but dedicated impact, her work is notable for tackling a practical, persistent challenge in the field—making colour calibration both efficient and reliable. Henderson’s approach demonstrates a keen ability to bridge theoretical segmentation techniques with applied robotics, offering a solution that reduces downtime and improves autonomy. For students and researchers exploring sensor perception or adaptive vision systems, her paper remains a valuable reference for automating a task often overlooked in robotics pipelines.
Research Focus
Key Achievements
Top Papers
- 1