# Automated Management of Pothole related Disasters Using Image Processing and Geotagging

arXiv: https://arxiv.org/abs/1610.08808 · HTML: https://mlsanity.com/paper/1610.08808/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 8 Jan 2016.

## Built on by (most cited first, 1 of 1)

- [Road Rutting Detection using Deep Learning on Images](https://mlsanity.com/paper/2209.14225/) (2022)

## Abstract (arXiv)

Potholes though seem inconsequential, may cause accidents resulting in loss of human life. In this paper, we present an automated system to efficiently manage the potholes in a ward by deploying geotagging and image processing techniques that overcomes the drawbacks associated with the existing survey-oriented systems. Image processing is used for identification of target pothole regions in the 2D images using edge detection and morphological image processing operations. A method is developed to accurately estimate the dimensions of the potholes from their images, analyze their area and depth, estimate the quantity of filling material required and therefore enabling pothole attendance on a priority basis. This will further enable the government official to have a fully automated system for effectively managing pothole related disasters.