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GithubSingTown's intelligent camera system, based on OpenMV, enables precise identification of linear features such as ground tile seams, cement joints, and black lines. Leveraging AI and machine vision technologies, the system can stably detect lines in complex lighting and multi-material ground environments, providing reliable visual navigation and positioning support for cleaning robots, line-following vehicles, and construction inspection systems.

In applications such as intelligent cleaning, automatic line following, and building inspection, accurately identifying ground black lines, tile seams, or cement seams is a crucial foundation for achieving path planning and surface detection. SingTown Technology's AI smart camera solution, based on the OpenMV platform, integrates machine vision and image recognition algorithms to develop an embedded vision system capable of real-time detection and tracking of ground line features.
After the system captures ground images through a high-frame-rate camera, AI algorithms analyse colour, brightness, and texture features to accurately extract linear targets such as black lines, cement joints, and tile seams. Even in the presence of ground reflections, complex patterns, or dust interference, the system maintains stable recognition. The recognition results can be transmitted in real-time to the control system for applications such as robot line-following navigation, ground flatness detection, or automated repair guidance.
The OpenMV intelligent camera features low power consumption, compact size, and high responsiveness, making it suitable for integration into cleaning robots, inspection vehicles, or intelligent construction monitoring equipment. Its edge deployment advantage leverages the camera and on-device AI to provide continuous visual guidance and feedback. Through computer vision technology, the system can further calculate line direction, width, and positional deviation, enabling higher-precision path correction.
SingTown Technology deeply integrates AI with machine vision, enabling smart cameras not only to "notice ground seams" but also to "understand paths." This solution is widely applicable in scenarios such as automated line inspection, ground detection, and indoor navigation, providing stable, precise, and high-efficiency visual recognition capabilities for smart devices.

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