| Authors | DR. JYOTI. Y. KULKARNI |
|---|---|
| Article Type | Research Article |
| Language | English |
| Journal | North Asian International Research Journal of Multidisciplinary |
| ISSN | 2454-2326 |
| Volume | 10 |
| Issue | 11 |
| Pages | 17-27 |
| Publication Year | 2024 |
| Publication Date | November 01, 2024 |
| DOI URL | https://doiglobal.org/10.2024/NAIRJCMD.051 |
Potholes are a recurring pavement defect that affects ride quality, vehicle operating cost and road safety. Conventional field inspection requires personnel to identify defects and manually measure their dimensions, making large-scale surveys time-consuming and potentially hazardous. This paper presents an image-based framework for pothole detection and size estimation on Indian roads using digital image processing techniques. The proposed methodology combines road-image acquisition, grayscale transformation, denoising, contrast enhancement, edge extraction, adaptive segmentation, morphological processing, contour analysis and geometric calibration. Pothole length, width and image-plane area are obtained from segmented contours and converted from pixels to physical units through a calibrated reference or perspective-aware scale. The paper emphasizes that monocular pixel measurements cannot be treated as real-world dimensions without calibration because camera height, pitch and perspective alter apparent size. Published benchmark studies are used only for comparative discussion: a 2020 UAV image-processing study reported 80% precision and 74.4% recall; a 2024 YOLO-based dimension-estimation study reported 93.0% precision, 91.6% recall, 87.0% F1-score and 96.3% mAP; and a 2025 segmentation-plus-inverse-perspective-mapping study reported an average dimension-estimation error of 11.30%. The proposed classical image-processing workflow is positioned as a low-cost and interpretable baseline suitable for controlled road imagery, with deep learning suggested as an extension for complex shadows, patches and heterogeneous pavement textures. The study concludes that reliable pothole measurement requires not only segmentation accuracy but also careful geometric calibration and field validation.
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DOI: 10.2024/NAIRJCMD.051
Journal:
North Asian International Research Journal of Multidisciplinary
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DOIGLOBAL
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