Papers
4
Total Citations
34
H-Index
3
About
Abed Malti is a researcher whose work sits at the intersection of computer vision, robotics, and precision imaging. His primary research areas include feature detection and matching, sensor-based motion planning, and the calibration of advanced imaging systems. One of his most significant contributions is in addressing the challenges of radial distortion in images, where he developed robust methods for keypoint matching that are critical for applications like 3D reconstruction, SLAM, and visual servoing—work that has garnered 19 citations. Malti has also made notable strides in the calibration of scanning electron microscopes (SEM), tackling the complex issue of image drift over time and magnification, a problem that directly impacts nanoscale imaging accuracy. His work on landmark-based motion planning for mobile robots introduces a general framework for automatically selecting relevant landmarks to correct trajectories and ensure smooth navigation. With a career spanning foundational problems in both macroscopic robotics and microscopic imaging, Malti’s research demonstrates a rare ability to bridge theoretical algorithms with practical, high-precision applications.
Research Focus
Key Achievements
Top Papers
- 1Feature detection and matching in images with radial distortion19 citations · 2010
- 2
- 3Planning Robust Landmarks for Sensor Based Motion3 citations · 2008
- 4