Precision Inspection Enters the AI Era: SingTown Technology Makes Micron-Level Measurement Easier

In the process of precision component machining and assembly, the hole position coordinates and angular orientation of the workpiece are critical parameters for ensuring assembly accuracy and consistency.

Manual measurement suffers from significant errors, low efficiency, and difficulty in adapting to automated production.

為此，精密製造企業採用SingTown的OpenMV智能相機識別技術，結合AI機器視覺與幾何計算算法，實現對工件圓孔坐標位置及其整體角度的實時檢測與輸出。

This solution can be widely applied in scenarios such as PCB board inspection, metal component hole alignment calibration, and automated assembly positioning, significantly enhancing the precision and automation level of industrial production.

精密製造企業運用SingTown Technology嘅OpenMV智能相機識別技術，實現對小型工件圓孔座標同角度姿態嘅自動檢測。

A high-resolution camera is installed on a fixed inspection platform to capture images of a 53×40mm inspection board.

The system automatically extracts the contour of circular holes on the board surface using an edge detection plus circular recognition (Hough Transform) algorithm, and calculates the centre coordinates (x, y) and diameter dimensions (approximately 4.20 mm).

Subsequently, the rotation angle of the entire panel relative to the reference direction is automatically determined using the minimum bounding rectangle angle analysis method, thereby achieving angle posture detection.

Upon completion of identification, the OpenMV module can output measurement results in real-time to the host computer or PLC system via UART/USB interfaces, enabling robotic arms to perform assembly calibration or position compensation.

The system supports adaptive illumination, edge sharpening, and sub-pixel fitting technology, enabling stable measurement of circular hole coordinates and angular deviations within an accuracy range of ±0.05mm.

This solution utilises computer vision and image recognition technologies to achieve high-precision geometric inspection and automatic calibration of small workpieces under edge deployment conditions, significantly enhancing the efficiency and reliability of inspection in precision manufacturing processes.