Publication Type : Conference Paper
Publisher : IEEE
Source : 2023 Third International Conference on Artificial Intelligence and Smart Energy (ICAIS)
Url : https://doi.org/10.1109/icais56108.2023.10073915
Campus : Chennai
School : School of Computing
Department : Computer Science and Engineering
Year : 2023
Abstract : Visual simultaneous localization and mapping (SLAM), which has numerous potential uses, is swiftly emerging as a significant development in embedded vision. In our analysis, there remain several unsolved dilemmas about SLAM that are visual, making it less favored over Lidar SLAM. Because it offers an affordable solution for mapping and navigation in mobile robots. These mobile robots can be defined as robots whose unique base is not fixed, so as technology establishes and advances, we. In this report, a real-time light, that is, dim or image or video in low light problem enhancement algorithm is proposed that significantly improves the overall performance of the Canny Edge part detection algorithm, which usually may be useful for benefit recognition in low light issues in cellular robots for several mapping and navigation tasks.
Cite this Research Publication : Pradeep Surya Dadi, Saranya G, Tamilvizhi T, Leema Nelson, Surendran R, Improved Performance of Canny Edge Detection in Low-Light Conditions, 2023 Third International Conference on Artificial Intelligence and Smart Energy (ICAIS), IEEE, 2023, https://doi.org/10.1109/icais56108.2023.10073915