OpenMV
Shields
Lens
Robotics
Book
Video
Download
Docs
Forum
OpenMV.io
GithubOn industrial electronic equipment assembly lines, product panels typically contain various components such as knobs, labels, buttons, and accessories. Manual quality inspection methods are prone to misjudgment, missed detection, and low efficiency.
Therefore, industrial electronic assembly manufacturers adopt SingTown's OpenMV intelligent camera to construct a smart visual inspection system, enabling automatic recognition and judgment of font printing content and angle, knob position, and component installation status. The system's inspection range is 350mm in length and 150mm in width, with the camera installed within a distance of 200mm, allowing for simultaneous multi-item inspection within limited space.
This solution can be widely applied in scenarios such as electronic control panels, switchgear, and assembly lines for precision instrument housings, assisting enterprises in achieving efficient and automated quality inspection.

Industrial electronics assembly manufacturers have developed a machine vision inspection system based on the OpenMV smart camera, integrating computer vision, AI image recognition, template matching, and OCR character detection algorithms to achieve real-time inspection of complex panel assemblies.
This embedded vision system captures partial product images via high-definition cameras, performs OCR text recognition and tilt angle analysis on label areas to determine whether text is misapplied, misaligned, or exhibits color anomalies; simultaneously, it employs geometric feature matching algorithms to detect whether knob angles and positions comply with standards. For accessories of different colors (such as yellow and gray small components), the system can automatically assess whether installation is correct through color segmentation and morphological analysis.
Furthermore, template comparison can detect abnormalities such as foreign objects, dropped items, and missing installations. It completes the judgment within the detection cycle (within 5 seconds) and outputs signals to the PLC or host computer, enabling automatic rejection of defective products.
This solution offers advantages such as high detection accuracy (error <0.1mm), fast response speed, strong environmental adaptability, and edge deployment, making it widely applicable in electronic assembly and consistency control scenarios.

AI Sentinel Based on OpenMV: Automatic Alert for Unsecured Key Locations
Automatically detects whether the doors of key locations remain open for an extended period and issues timely alerts.

Personnel crossing boundary triggers an alarm; OpenMV interprets the “sense of security boundary”
Detects personnel or equipment crossing virtual perimeter lines.

“AI Urban Management Officer” is here: an automatic encroachment operation identification system built on OpenMV
Automatically identifies illegal street vending activities to support daily urban governance.

Improper placement of gas cylinders? Use OpenMV to automatically trigger hazard alerts
Automatically identifies unauthorized placements of gas cylinders to proactively detect potential gas safety hazards.

Did you perform live-line work without wearing insulating gloves? OpenMV issues an immediate alert!
Automatically identifies whether personnel are wearing insulating gloves to assist in safe operations.

Utilize the OpenMV smart camera to perform real-time detection of surface defects on aluminum plates
Online identification of surface defects on aluminum plates, such as scratches and dents, to support quality control.