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INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT International Peer Reviewed & Refereed Journals, Open Access Journal ISSN Approved Journal No: 2456-4184 | Impact factor: 8.76 | ESTD Year: 2016 Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.76 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI) |
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| Paper Title: | Pothole Detection Using Dashcam |
| Authors Name: | Deep Sheth , Pratik Shahdadpuri , Vivek Sevak , Arzoo Busa , Shivendra Dubey |
| Download E-Certificate: | Download |
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IJNRD_215602
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| Published Paper Id: | IJNRD2403257 |
| Published In: | Volume 9 Issue 3, March-2024 |
| DOI: | |
| Abstract: | Potholes are a common problem in road infra-structure and can lead to accidents, vehicle damage, and traffic congestion. In recent years, with the increasing availability of dash cameras in vehicles, there has been growing interest in using them to automatically detect and report potholes on the road. This paper presents an approach for pothole detection using dash cameras, which involves capturing video footage of the road and processing it using computer vision techniques. The proposed approach uses a combination of image processing algorithms and machine learning techniques to detect and classify potholes from the video stream. The algorithm first extracts frames from the video and applies a pre-processing step to enhance the contrast of the images. It then uses edge detection and texture analysis techniques to identify regions that potentially contain potholes. These regions are further processed using a deep learning model to classify them as either potholes or non-potholes. The experimental results show that the proposed approach can accurately detect potholes in real-time with high precision and recall rates. The approach is also tested on a large data set of road images captured from different dash cameras and is found to be robust to different lighting and weather conditions. The proposed approach has the potential to provide a low-cost and efficient solution for pothole detection and can be integrated into existing dash camera systems. The system can then alert drivers to the presence of potholes and help road maintenance authorities to quickly identify and repair potholes before they cause accidents or damage to vehicles. |
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| Cite Article: | "Pothole Detection Using Dashcam", International Journal of Novel Research and Development (www.ijnrd.org), ISSN:2456-4184, Vol.9, Issue 3, page no.c448-c453, March-2024, Available :http://www.ijnrd.org/papers/IJNRD2403257.pdf |
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| ISSN: |
2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar| ESTD YEAR: 2016 An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.76 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator |
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Published Paper ID:IJNRD2403257 Registration ID: 215602 Published In: Volume 9 Issue 3, March-2024 DOI (Digital Object Identifier): Page No: c448-c453 Country: Vadodara, Gujarat, India Research Area: Computer Science & Technology Publisher : IJ Publication Published Paper URL : https://www.ijnrd.org/viewpaperforall?paper=IJNRD2403257 Published Paper PDF: https://www.ijnrd.org/papers/IJNRD2403257 |
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ISSN: 2456-4184
Impact Factor: 8.76 and ISSN APPROVED
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