How a VisionMaster solution is built
HIKROBOT VisionMaster (written as HIKROBOT Vision Master software in some vendor material) builds an inspection as a graphical solution: tools are linked in a flow, from acquiring the image through locating the product, inspecting it and combining the results, to sending one result to the PLC. HIKROBOT describes tool groups for locating and measuring, identification, defect detection and registration learning, alongside deep-learning modules, and lists TCP/IP, Modbus, serial, UDP and EtherNet/IP among its communication protocols (HIKROBOT catalogue 2025 Q4). addaScan builds stations on VisionMaster for plants in South Africa as an independent integrator; this website does not claim any official HIKROBOT partnership or distributor status.
Tool groups and where each applies
These are the machine vision algorithms VisionMaster provides, in HIKROBOT’s groups. The tools in the second column are named as HIKROBOT lists them (HIKROBOT catalogue 2025 Q4). Where each applies, and its limits, is our engineering view.
| Tool group | Tools (HIKROBOT naming) | Applies to | Limit |
|---|---|---|---|
| Locating | Template and feature matching (pattern matching), mark locating, position fixture, blob analysis, circle, line, edge and rectangle search, caliper | Find the product or a feature so that every other tool follows it when the product shifts or rotates | Needs a stable, distinctive feature to lock on to |
| Measurement | Point, line and circle distance measurements, edge distance, intensity, pixel count, histogram | Dimensions, gaps and positions; fill level from an edge; cap height; label position | Accuracy depends on optics, calibration and presentation |
| Identification | 1D and 2D code reading, including deep-learning code reading; OCR, including deep-learning character recognition | Barcodes, DataMatrix and QR codes, date and batch codes, printed and marked text | Reading is not grading print quality |
| Defect detection | Deep-learning surface defect detection, contour defect detection, comparison with a standard part | Scratches, spots, dirt, broken edges, incomplete contours and character defects | Needs labelled defect images and a validation set |
| Registration learning | Register-classify, register-category and register-detect: online learning from a few registered images, on CPU or GPU | Variant and wrong-SKU checks, simple classification and detection without offline training | Suits clear differences; verify on unseen samples |
| Deep-learning modules | Classification, object detection, image segmentation and related modules in the deep-learning package | Variable defects on natural or textured surfaces, counting irregular objects, defect area measurement | More images, training and retraining effort |
Typical inspections and the tools behind them
Most packaging and parts inspections combine two or three tool groups. These are the combinations we use most often; the final choice is made on your samples.
| Inspection | Tools | Application page |
|---|---|---|
| Label present, straight, right SKU | Locating + measurement for position; registration classification or code reading for the SKU | Label inspection |
| Date and batch code correct and legible | Locating + OCR (deep-learning OCR on difficult print) + character comparison with the expected string | OCR/OCV inspection |
| Fill level and cap height | Edge search and measurement against a backlight | Fill level and cap inspection |
| Missing parts and counts | Blob analysis, pattern existence and counting; object detection for irregular items | Presence and counting |
| Scratches and marks on moulded or metal parts | Deep-learning defect detection, with locating first | Surface defect detection |
| Hole positions, diameters, gaps | Circle and line search, caliper, point-to-line and circle-to-circle measurement | Dimensional inspection |
| DataMatrix marked on parts | Deep-learning code reading with lighting for the mark | DPM code reading |
Which tools run on which HIKROBOT device
Not every device runs every tool. HIKROBOT’s capability table for its smart cameras shows the step-up by series (HIKROBOT catalogue 2025 Q4). VisionMaster on a PC or vision controller has the full tool set, including the VisionMaster deep learning package.
| Capability | SC1000 | SC2000E | SC3000X | SC5000X / SC6000 |
|---|---|---|---|---|
| Existence, count, basic measurement, logic | Yes | Yes | Yes | Yes |
| Pattern existence and count | No | Yes | Yes | Yes |
| OCR and character comparison | No | Yes | Yes | Yes |
| Code recognition, match location | No | No | Yes | Yes |
| DL classification and object detection | No | No | Yes | Yes |
| DL image segmentation | No | No | No | Yes |
| Module limit per solution | 20 | 40 | 40 | 1024 |
Rules, deep learning or registration learning
- Rule-based tools (locating, measurement, code reading, blob analysis) for faults that can be written as a measurement or rule. They are quick to validate and stable.
- Registration learning for clear differences learned from a few images, such as product variants, when there is no time or data for full training.
- Deep learning for defects that vary in shape and appearance on a variable surface, with labelled images and a retraining plan.
Most solutions mix them: locate with rules, read codes with rules, and use deep learning only on the region where fixed rules fail. See rule-based or deep learning and the commissioning procedure.