Nikitha Rao
Papers
1
Total Citations
1
H-Index
1
About
Nikitha Rao is a researcher at the forefront of computer vision and video analytics, with a specialized focus on morphological image processing techniques. Her most-cited work, "Comparative Analysis of Morphological Functions for Object Detection in Video Processing" (2024), provides a rigorous evaluation of how different morphological operators—such as dilation, erosion, opening, and closing—affect the accuracy and efficiency of object detection in dynamic video streams. This study offers practitioners a clear, data-driven framework for selecting optimal preprocessing methods, directly impacting real-time surveillance, autonomous navigation, and industrial inspection systems. While her citation count is currently modest, the paper’s practical relevance and methodological clarity position it as a foundational reference for engineers and researchers working to enhance detection robustness against noise and varying lighting conditions. Rao’s contribution lies in bridging the gap between theoretical morphology and applied video processing, delivering actionable insights that reduce computational overhead without sacrificing detection performance. Her work is particularly valuable for students and professionals seeking to understand the trade-offs between different morphological pipelines, making her a rising voice in the field of intelligent video analysis.
Research Focus
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Top Papers
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