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Computer vision model to detect pavement cracks in drone imagery A brief summary of the item is not available. Add a brief summary about the item.

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Item created: Feb 14, 2022 Item updated: Jan 2, 2025 Number of downloads: 3,187

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Description

This model detects pavement cracks and potholes in drone imagery. Such deterioration of road surfaces may be caused by poor construction, heavy load or weather factors. This negatively affects road safety, driving comfort, and the wear and tear of vehicles. Civic authorities need to accurately identify these cracks and perform repair work. If these cracks are not repaired at an early stage, the cost of repair escalates quickly.

Traditionally, inspection of road surface is done by human inspectors or by using sophisticated machines which are accurate but very expensive. This model can automate the pavement inspection process using drone imagery, and enable better monitoring and maintenance of roads.

Using the model
Follow the guide to use the model. To use this model, ensure that the supported deep learning libraries are installed. For more details, check Deep Learning Libraries Installer for ArcGIS. This is a computer vision model and cannot be fine-tuned.

Fine-tuning the model
This model cannot be fine-tuned using ArcGIS tools.

Input
This model is expected to work on high resolution drone imagery in the form of a raster, mosaic dataset, or image service. The preferred cell size is under 2 centimeters per pixel.

Output
Feature class containing detected pavement cracks.

Applicable geographies
The model is expected to work globally.

Model architecture
The model is implemented using computer vision techniques. 

Accuracy metrics
This model is implemented using computer vision techniques and due to non availability of ground truth data, accuracy metrics are not available. The model cannot be fine-tuned. 

Sample results
Here are a few results from the model.





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https://downloads.esri.com/blogs/arcgisonline/esrilogo_new.png This work is licensed under the Esri Master License Agreement.

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          ID: a9c3134e361e49a191efda169f5a337d

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          pavement cracks, deep learning, Deep Learning Package, livingatlasdlpk, cracks, roads, detection

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