Dynamic Imaging Detection and Target Recognition for Cat-Eye Effect Echo

Dongsheng, 武东生 Wu; Tingzhu, 白廷柱 Bai; Bingqi, 刘秉琦 Liu; Bin, 周斌 Zhou; Wengang, 胡文刚 Hu

doi:10.3788/aos201333.0811003

Cited by 3 publications

(2 citation statements)

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“…In general, traditional cat-eye target detection systems are developed based on bistatic optical designs [4], [9], [10], where the transmitting and receiving optical axes are separated. These systems perform well when detecting larger, traditional cat-eye targets, but do not perform well when detecting mini-cameras.…”

Section: Optical System Designmentioning

confidence: 99%

“…Traditional active laser detection systems utilize the chatoyancy effect, in which the laser beam is reflected directly back to the laser source by hidden camera lenses and the power of this retroreflection is significantly higher than that of the diffuse background signal [1]- [4]. However, when detecting mini-cameras, there are several limitations: (1) The size of the lens aperture of a minicamera is so small that the reflection is too weak to stand in stark contrast with the background;…”

Section: Introductionmentioning

confidence: 99%

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Design of an Active Laser Mini-Camera Detection System Using CNN

et al. 2019

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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 minicameras 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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Section: Optical System Designmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Design of an Active Laser Mini-Camera Detection System Using CNN

et al. 2019

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A new displacement demodulation algorithm for the phase-modulated self-mixing interferometer based on FPGA

Liu

Fangming

Wencai

et al. 2021

Procedia Computer Science

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Analysis of Mini-Camera's Cat-Eye Retro-Reflection for Characterization of Diffraction Rings and Arrayed Spots

et al. 2019

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Mini-cameras are one of several emerging types of cat-eye devices using small lenses with insufficient retro-reflection for traditional detection systems to identify. Based on a structural analysis of these devices, this paper provides an accurate theoretical description of the received beam profile. The simulated and experimental results have good similarity in terms of profile shapes and trends with different incident angles and defocus distances. An analysis of the detection conditions and the reflection image features described in this article can thus be applied to hidden camera detection. Mini-cameras can be detected according to these features of the received beam profiles.

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Dynamic Imaging Detection and Target Recognition for Cat-Eye Effect Echo

Cited by 3 publications

References 0 publications

Design of an Active Laser Mini-Camera Detection System Using CNN

Design of an Active Laser Mini-Camera Detection System Using CNN

A new displacement demodulation algorithm for the phase-modulated self-mixing interferometer based on FPGA

Analysis of Mini-Camera's Cat-Eye Retro-Reflection for Characterization of Diffraction Rings and Arrayed Spots

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