Computer Vision

Computer Vision

Computer Vision

For whom

For companies in food, pharma, agriculture, petroleum or manufacturing that need to inspect, measure, sort or verify products visually (shape, color, surface, defects, count or 3D geometry) and want that turned into an automated, camera-based system instead of manual inspection.

When this is relevant

Use this when a human eye (or a lab test) is currently the bottleneck for quality control, sorting, defect detection or authenticity verification, or when you need real-time, on-line inspection at production speed rather than sampled, after-the-fact checks. Also relevant when spectroscopy alone tells you what something is chemically, but you also need to see how it looks: shape, surface defects, foreign objects, fill level, packaging integrity, or spatial dimensions.

The decision it helps you make

Decide whether a computer vision system is technically feasible for your inspection or sorting problem, which imaging approach fits (standard camera, 3D/depth sensing, structured light, multispectral or combined with NIR/Raman), and whether to invest in building and integrating that system in-house or bring in outside development.

What Vibralytics does

Vibralytics designs and develops the imaging and computer vision pipeline needed to turn a camera feed into an automated decision, from selecting the right imaging setup (standard, 3D/depth sensing, structured light or multispectral) through image processing, feature and edge detection, segmentation, object tracking and 3D reconstruction, to the classification or deep-learning model that makes the final call. Where relevant, this can be combined directly with Vibralytics’ spectroscopy and chemometrics work, so a single system can judge both what a product looks like and what it’s made of. Vibralytics also builds the software and interface layer so the output is a clear, usable result for the operator, not raw image data.

What you receive

  • Feasibility assessment for your specific inspection, sorting or measurement problem
  • Selected imaging approach (2D, 3D/depth, structured light or multispectral) matched to the task
  • Developed and validated computer vision model (detection, segmentation, classification or measurement)
  • Integration-ready model and software, with a user-friendly interface
  • Option to combine vision with NIR/Raman/FTIR data for a combined look and composition system
  • Report and documentation of methodology and performance

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