How can a pallet recycler or warehouse use computer vision to sort returned pallets into reuse, repair or scrap?

---
title: "How to grade used wooden pallets with computer vision"
description: "Photograph each returned pallet from the top and bottom as it moves along a conveyor or sits at a sorting station, then use a model trained on the company own graded pallet images to mark broken or missing boards, cracked blocks or stringers, protruding nails, heavy stains and the pallet type. The model suggests a grade, and a trained sorter confirms or changes it before the pallet moves on. It only speeds up sorting; people make the final grade call, and any pallet with a safety concern is pulled for a closer look."
url: https://lidvizion.ai/answers/how-to-grade-used-wooden-pallets-with-computer-vision/
site: Lid Vizion
index: https://lidvizion.ai/llms.txt
---

[Direct answers](https://lidvizion.ai/answers/)

# How can a pallet recycler or warehouse use computer vision to sort returned pallets into reuse, repair or scrap?

Photograph each returned pallet from the top and bottom as it moves along a conveyor or sits at a sorting station, then use a model trained on the company own graded pallet images to mark broken or missing boards, cracked blocks or stringers, protruding nails, heavy stains and the pallet type. The model suggests a grade, and a trained sorter confirms or changes it before the pallet moves on. It only speeds up sorting; people make the final grade call, and any pallet with a safety concern is pulled for a closer look.

## What this means in practice

- Set up cameras and steady lighting at the sorting point so the top and bottom of each pallet are captured the same way
- Collect images of pallets that experienced sorters have already graded as reuse, repair or scrap
- Label the damage types and pallet types the company tracks
- Show sorters the marked images and suggested grade, and record their final call
- Add sorter-reviewed images back into training whenever new pallet types or customers come in

## How Lid Vizion approaches it

We start with the business decision and operating context, define ownership and measurable milestones, then use configuration, integrations, automation, or custom software only where each earns its place.

## More on Automation & custom AI

- [How can a railroad or transit agency use computer vision to review track inspection images?](https://lidvizion.ai/answers/how-to-review-rail-track-inspection-images-with-computer-vision/)
- [How can a grower use computer vision to count fruit or grape clusters before harvest?](https://lidvizion.ai/answers/how-to-count-fruit-in-orchards-and-vineyards-with-computer-vision/)
- [How can a ship operator or yard use computer vision to review hull video from divers or underwater drones?](https://lidvizion.ai/answers/how-to-review-ship-hull-inspection-video-with-computer-vision/)

[Compare services](https://lidvizion.ai/services/) · [Use a planning tool](https://lidvizion.ai/tools/) · [Explore workflow use cases](https://lidvizion.ai/use-cases/) · [More direct answers](https://lidvizion.ai/answers/)

Talk it through

## Have a version of this question inside your company?

Bring the decision, the constraints, and what a good outcome looks like.

[Talk through the decision](https://lidvizion.ai/contact/?need=ai-workflow&from=%2Fanswers%2Fhow-to-grade-used-wooden-pallets-with-computer-vision%2F#write) · [Book a call](https://calendar.app.google/bB26LdA9e2gmGFp69)