---
title: "How to inspect work gloves with computer vision"
description: "A camera station looks at each work glove after knitting, dipping or sewing and flags holes, dropped stitches, thin or uneven coating, drips, missing fingertips, loose cuffs and pairs that do not match for a person to check. Each flag is saved with a photo and the line and batch, so repeat problems point back to a machine or a coating tank. A quality lead decides every pass or rework, and the usual cut, grip and wear tests stay in place."
url: https://lidvizion.ai/answers/how-to-inspect-work-gloves-with-computer-vision/
site: Lid Vizion
index: https://lidvizion.ai/llms.txt
---

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

# How can a glove maker use computer vision to inspect knit and coated work gloves?

A camera station looks at each work glove after knitting, dipping or sewing and flags holes, dropped stitches, thin or uneven coating, drips, missing fingertips, loose cuffs and pairs that do not match for a person to check. Each flag is saved with a photo and the line and batch, so repeat problems point back to a machine or a coating tank. A quality lead decides every pass or rework, and the usual cut, grip and wear tests stay in place.

## What this means in practice

- A camera and even light take pictures of the palm and back of each glove as it comes off the knitting machine, the coating line or the sewing table, often while it sits on a hand form.
- The model is trained on the clients own gloves and coatings. It flags holes, dropped or loose stitches, thin, bare or uneven coating, drips and bubbles, missing or short fingertips, loose cuffs, and left and right gloves that do not match in size or color.
- Each flag is saved with a photo, the line, machine and batch, and the time, so the team can see if one knitting head, form or coating tank keeps causing the same problem.
- A quality lead checks every flagged glove and decides whether it ships, gets fixed or is pulled. The camera points at the gloves, not at workers, and any people caught in view are blurred.
- Start with one line and one glove style, compare the camera flags with what the inspectors find for a few weeks, and keep the existing cut, grip, wear and label tests in place.

## 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

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- [How can a jewelry maker or seller use computer vision to inspect finished pieces?](https://lidvizion.ai/answers/how-to-inspect-jewelry-with-computer-vision/)

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