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Collit Technologies

Computer Vision

Defects are checked by eye, and some slip through.

  • Semiconductor & electronics
  • Medical & healthcare
  • Biotech & life sciences
  • Manufacturing
  • Security
  • Agriculture & food

Updated

Problem & solution

The problem

  • Inspection by eye

    Results vary by inspector and shift, with no record.

  • Defects found too late

    Caught at end of line or by the customer, when it costs most.

  • Hours of footage

    Finding one event means scrubbing video by hand.

How Collit solves it

  • Consistent checks

    The same rules on every image, every result saved.

  • Rules plus AI

    Classical vision where rules work, trained models where they don't.

  • Built for your samples

    Tuned to your materials, imaging and defect definitions.

  • Informed decisions

    Measurements and pass/fail results your team can act on.

Applications

  • Semiconductor & electronics

    Wafer and PCB defect inspection

    Microscope images are segmented to find, measure and classify defects.

  • Medical & healthcare

    Image analysis to support clinical review

    Regions of interest are highlighted for review; decisions stay with clinicians.

  • Biotech & life sciences

    Cell and colony counting

    Microscopy images are segmented and counted the same way every time.

  • Manufacturing

    Surface defect detection and QA

    Cameras at the station flag defects and log every part for traceability.

  • Security & surveillance

    Finding people or vehicles in recordings

    Detection runs over footage so you jump straight to the right moment.

  • Agriculture & food

    Grading and sorting produce

    Images grade items by size, colour and visible damage before packing.

How it works

  1. CaptureCamera, microscope or footage
  2. PrepareClean and normalise
  3. DetectFind regions of interest
  4. MeasureSize, count, classify
  5. ReviewResults your team acts on

Modules

Customizable and extensible: adapted to your workflow, with new modules added as you grow.

  • Reference alignment

    Match reference patterns to align inspection regions.

  • Regions of interest

    Define the areas of an image to inspect.

  • Thresholding

    Separate features from the background.

  • Image processing

    Apply thresholds, morphology, arithmetic and logic.

  • Blob detection

    Find and count regions of interest.

  • Measurements

    Size and position of what was found.

  • AI inference

    Run trained models on your images.

  • Anomaly detection

    Find deviations from learned reference images.

  • Edge detection

    Locate edges for inspection and measurement.

  • Rules

    Classify detections using configurable conditions.

  • Judgement

    Turn inspection results into pass or fail decisions.

  • Saved workspaces

    Reuse inspection settings.

  • Your module

    Built around your workflow.

What you get

  • Feasibility review on your sample images
  • Inspection or footage-search software
  • Reusable inspection settings
  • Result export to your systems
  • Operator training

What we validate with you

Proven on your own data during the pilot.

  • Written defect definitions
  • Image quality and lighting
  • Performance on your own samples
  • Pilot acceptance criteria

Q&As

Do you supply cameras, lighting and automation?

Our focus is the software. A complete machine vision system, with cameras, lighting and automation such as conveyors, robot arms or linear motors, is possible but needs a longer study and a larger budget.

How accurate will it be?

We measure accuracy on your own good and defective samples during the pilot, against criteria agreed with you.

How many images do you need?

A small set of good and defective examples is enough for a feasibility review.

Does our image data leave our premises?

It doesn't have to. Inspection can run on your own computers.

Tell us what's slowing you down

Free 30-minute discovery call. No obligation.

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