Introduction

You are viewing an old version of the documentation. You can switch to the documentation of the latest version by clicking the top-right corner of the page.

The Unsupervised Segmentation algorithm can be used to judge whether the image of an object is OK, NG, or Unknown on the basis of set thresholds. Moreover, heat maps are available to show the possible areas with defects.

  • If the Defect confidence of an image is less than the threshold set for OK results, the image will be labeled as OK.

  • If the Defect confidence of an image is greater than the threshold set for NG results, the image will be labeled as NG.

  • If the Defect confidence of an image is greater than the threshold set for OK results and less than the threshold set for NG results, the image will be labeled as Unknown.

Application Scenario

Quality inspection: The algorithm is applicable to scenarios where objects have defects of different shapes and size and in different positions but their OK images have small but important differences.

uncertain defects

General Workflow

introduction application flow

We Value Your Privacy

We use cookies to provide you with the best possible experience on our website. By continuing to use the site, you acknowledge that you agree to the use of cookies. If you decline, a single cookie will be used to ensure you're not tracked or remembered when you visit this website.