Dorra Sellami
Papers
1
Total Citations
5
H-Index
1
About
Dorra Sellami is a researcher specializing in reconfigurable computing and real-time image processing, with a particular focus on FPGA-based architectures for morphological operations. Her most cited work, "A Highly Flexible Architecture for Morphological Gradient Processing Implemented on FPGA" (2019), introduces a novel, adaptable hardware design that efficiently computes morphological gradients—a critical step in edge detection and feature extraction for computer vision. This contribution stands out for its flexibility, enabling dynamic reconfiguration to handle varying image sizes and kernel shapes without sacrificing speed, a key advantage for embedded and high-throughput applications. With 5 citations, this paper has influenced subsequent work in hardware acceleration for image processing, demonstrating the growing demand for efficient, real-time solutions in fields like medical imaging and autonomous systems. Sellami’s research bridges the gap between algorithmic complexity and hardware efficiency, offering practical pathways for deploying advanced image analysis on resource-constrained platforms. Her work is particularly valuable for students and engineers exploring the intersection of digital design and computer vision, showcasing how FPGA-based implementations can unlock new performance levels for real-world applications.
Research Focus
Key Achievements
Top Papers
- 1