10.46243/jst.2020.v5.i3.pp101-110 registered
Detection of Pothole by Image Processing Using UAV
Resolves to https://www.jst.org.in/index.php/pub/article/view/389
Held by Longman Publishers (India) · prefix 10.46243 live · DOI address https://doi.org/10.46243/jst.2020.v5.i3.pp101-110
Registered 29 Sep 2026 via crossref · record version 2 · last change 29 Sep 2026, 11:59 PM · record sha256 9cd6336e7c23317e…
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What the DOI identifies
JournalArticle — an article in a journal · Digital · Visual · en
Detection of Pothole by Image Processing Using UAV (PrincipalTitle)
Published 2020-05-13
Part of Journal of Science & Technology · ISSN 2456-5660 · volume 5 · issue 3
Agents
- Saurabh Pehere (author) · Department of Electronics &Telecommunication, Pimpri Chinchwad College of Engineering Pune, India
- Prajwal Sanganwar (author) · Department of Electronics &Telecommunication, Pimpri Chinchwad College of Engineering Pune, India
- Shashikant Pawar (author) · Department of Electronics &Telecommunication, Pimpri Chinchwad College of Engineering Pune, India
- Prof. Ashwini Shinde (author) · Assistant.Professor, Department of Electronics &Telecommunication, Pimpri Chinchwad College of Engineering, Pune, India
- Longman Publishers (publisher)
Identifiers DOI 10.46243/jst.2020.v5.i3.pp101-110
Abstract
Potholes on road can generate costly damage to flat tire or can cause wheel damage of motor cycle. Especially in India vehicle collision and major accidents happens due to immense depth of pothole on road. Thus, detecting and repairing of potholes on road is major challenge for in ITS (Intelligent Transportation System) service and road management system. In order to enhance the efficiency of pavement inspection,currently some new sorts of remote sensing methods without any physical damage to the pavements is possible. In our study the pavement images captured by the unmanned aerial vehicle are collected and distinguish the pavements with the pothole from the normal pavements by performing the Morphological Operations on the images. UAV is new tool under the Remote sensing technique for the pavement inspection with more efficiency as it is usable in hard to reach places also where road maintenance is difficult. Through large transport surveillance, we built a method that can detect pothole using various algorithms of image processing for time optimization of surveillance. A model of potholes is constructed using the image library, which is used in an algorithmic approach that combines a live road footage and simultaneously detection of potholes using simple image processing techniques such as a medium filter and edge detection. Using this approach, it was possible to detect potholes with a precision of 80% and recall of 74.4.%. Using UAV, we can reach in remote places and specially to National Highways, detection of pothole and collecting all database become very easy and time saving. With more advanced technologies such as Artificial Intelligence and Machine Learning algorithms can be used for surveillance of road with more precise results with automatic repairing robots or machines
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Each element by the standard's name (Annex B: reference elements, then administrative) and the Handbook's (in grey), read off the record above.
| Element | Value | In the record |
|---|---|---|
| DOI Name DOI name | 10.46243/jst.2020.v5.i3.pp101-110 | doi |
| Referent Type referentType | Creation | referent |
| Referent Sub-Type referentSubType | JournalArticle — an article in a journal | type |
| Referent Name(s) referentName(s) | Detection of Pothole by Image Processing Using UAV (PrincipalTitle, en) | titles |
| Basic Metadata basicMetadata | author: Saurabh Pehere author: Prajwal Sanganwar author: Shashikant Pawar author: Prof. Ashwini Shinde publisher: Longman Publishers published: 2020-05-13 part of: Journal of Science & Technology · ISSN 2456-5660 · vol. 5 · no. 3 language: en form: Digital · Visual · Language | agents, dates, container, language, structural_type, modes, characters |
| Referent Identifier(s) alternateIdentifier(s) | none besides the DOI | identifiers, relations (IsSameAs) |
| Registration Authority registrationAuthorityCode | Crossref — issued by Crossref (member 25296); held here as a copy | record.source_agency (our code, ra_doi_name, for names issued here once appointed) |
| Created Date issueDate | 2020-05-13 | record.registered (when the DOI name was first registered) |
| relatedIdentifiers | none needed — the descriptive metadata is in this record | container, relations (only where the descriptive metadata lives at another identifier) |
complete Every System Metadata element is here, with the basic metadata a journal article needs.
Recommended for a journal article and not in this record: the first page or an article number · the reference list.
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History — the ledger
Every change to this DOI, in order, as it was recorded. Entries are only ever added, never changed or removed.
| # | When | What | By | Changes |
|---|---|---|---|---|
| 1 | 29 Sep 2026, 10:00 PM | register registered at Crossref; record read from api.crossref.org | Administrator (admin) | 74 fields set · sha256 090cc2600b23… |
| 2 | 29 Sep 2026, 11:59 PM | update record re-read from api.crossref.org | Administrator (admin) | container.titles.0.value: |
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