Cascaded Modules Commonly Used for AI-Based Quality Inspection

This topic introduces common cascaded modules in AI-based quality inspection and provides example projects for practice.

  1. Object Detection–Defect Segmentation (Click to download the example project)

    • Feature: Position the to-be-detected objects in an image and then detect defects.

    • Applicable scenarios: There are many objects to be detected in the original image, and the position and number of objects are random; the shapes of defects vary.

      object defectseg example

  2. Defect Segmentation–Defect Segmentation (Click to download the example project)

    • Feature: The Defect Segmentation module segments the region to be detected and the background, and then the Defect Segmentation module performs defect detection on the extracted region.

    • Applicable scenarios: Complex background, small or inconspicuous defects. The to-be-detected region should be extracted before fine defect detection.

      defectseg defectseg example

  3. Text Detection–Text Recognition (Click to download the example project)

    • Feature: The Text Detection module can position and extract the text areas of images to reduce the interference from the background and the text orientations. It cannot be followed by any other module.

    • Applicable scenarios: complex backgrounds and different text orientations.

      txt ocr example

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