A reliable vision project is not just an algorithm or a camera. It requires optics, algorithms, software, communication, mechanics and commissioning to work together.
Capabilities are defined by what can be delivered on site, covering imaging, inspection, recognition, measurement, communication and traceability.
Select cameras, lenses, lighting and mounting according to material, reflection, speed, space and accuracy.
Use edges, contours, templates, regions, morphology and geometry to solve positioning, measurement and inspection.
Improve robustness for complex surface defects and objects that are hard to describe with traditional rules.
Recognize inkjet codes, laser marks, serial numbers, QR codes and traceability codes with image evidence.
Convert image coordinates into usable dimensions and positions with calibration and sub-pixel geometry.
Send vision results to PLCs, robots, rejection devices, motion platforms or host systems to close the loop.
Build maintainable vision software covering permissions, parameters, logs, images, results, reports and interfaces.
Reliable machine vision requires sample evaluation, optical tests, algorithm validation, software architecture, equipment communication, acceptance and maintenance.
Evaluate samples and site constraints before choosing the algorithm route.
Prioritize stable imaging before algorithm complexity.
Key results must be recorded, traceable and reviewable.
Software must support parameter tuning, version updates and remote maintenance.
Send sample images, inspection requirements or site photos. We can review feasibility from optics, algorithms, takt, mechanics and communication.