The growing popularity of the mini-camera is posing a serious threat to privacy and personal security. Disguised as common tools in rooms, these devices can become undetectable. Moreover, conventional active laser detection systems often fail to recognize them owing to their small lens size, weak reflectivity, and the influence of interference targets. In this paper, a method for building a laser active detection system for mini-cameras is proposed. Using a monostatic optical system and a deep learning classification algorithm, this anti-camera system can detect mini-cameras accurately in real time. This article describes the system components including its optical design, core components and image processing algorithm. The capability of the system for detecting mini-cameras and identifying interference is also experimentally demonstrated. This work successfully overcomes the limit of mini-camera detection using deep learning methods in active laser detection systems.

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基于CNN的有源激光微型摄像机检测系统设计

迷你相机的日益普及正在对隐私和人身安全构成严重威胁。这些设备伪装成房间里的常用工具，可能无法检测到。此外，传统的主动激光探测系统由于其透镜尺寸小、反射率弱以及受干扰目标的影响，往往无法识别它们。本文提出了一种构建微型相机激光主动检测系统的方法。该反相机系统采用单站光学系统和深度学习分类算法，可实时准确检测微型相机。本文介绍了系统组件，包括其光学设计、核心组件和图像处理算法。还通过实验证明了该系统检测微型相机和识别干扰的能力。