Iqbaldeep Kaur
Papers
2
Total Citations
13
H-Index
2
About
Iqbaldeep Kaur is a researcher in computational image processing and computer vision, with a focus on thresholding-based techniques for enhanced image analysis. Her work addresses critical challenges in foggy and low-visibility environments, as demonstrated by her 2020 paper "FEMT: a computational approach for fog elimination using multiple thresholds," which has garnered 7 citations. She further advanced the field with "An efficient method of multicolor detection using global optimum thresholding for image analysis" (2021, 6 citations), introducing robust algorithms for accurate color segmentation in complex images. Kaur’s contributions lie in developing efficient, threshold-driven methods that improve image clarity and object detection, with applications in autonomous systems, surveillance, and medical imaging. Her research has been recognized for its practical utility, offering scalable solutions for real-world image degradation problems. By combining theoretical rigor with computational efficiency, Kaur continues to influence the development of adaptive thresholding techniques, making her work a valuable resource for students and researchers exploring image enhancement and pattern recognition.
Research Focus
Key Achievements
Top Papers
- 1
- 2