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GithubOpenMVShieldsLensRoboticsBookVideoDownloadDocsForumOpenMV.ioGithubSingTown AI Vision Technology enables more accurate, stable, and intelligent counting on packaging production lines.
In packaging production lines, conventional infrared or mechanical counting techniques are prone to interference from lighting, velocity, and object forms, resulting in imprecise tallies or response lags.
To enhance detection accuracy and automation levels, packaging equipment manufacturers have introduced SingTown's OpenMV intelligent camera AI image recognition technology. Utilising AI machine vision and image recognition algorithms, this system automatically detects and counts packaging bags on the conveyor belt, achieving real-time signal output and coordinated control.
The packaging counting system utilises SingTown Technology's OpenMV intelligent camera AI image recognition technology to monitor the quantity of packaging bags in real-time on the operating conveyor belt.
The camera is installed 1.5–2 metres away from the conveyor belt to capture images and perform edge AI recognition of packaging bags measuring approximately 70cm × 40cm. The system utilises computer vision algorithms (edge detection + motion recognition + target tracking) to determine the entry and exit status of the packaging. When a complete package is detected passing through the recognition area, it automatically outputs a counting signal.
The OpenMV intelligent camera enables flexible edge deployment, featuring edge computing capabilities and multiple I/O control interfaces. It can directly send pulse signals to PLCs, microcontrollers, or host computers via GPIO or serial ports, achieving production synchronisation and output statistics.
The system response time is below 20 milliseconds, ensuring stable adaptation to varying conveying speeds and lighting conditions.
Through SingTown Technology's OpenMV intelligent camera image recognition solution, packaging production lines have been upgraded from manual or photoelectric counting to AI visual counting, significantly enhancing detection accuracy, stability, and production efficiency.
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