The novel role of arctangent phase algorithm and voice enhancement techniques in laser hearing

Zhang, Heyong; Lv, Tao; Yan, Chun-Hui

doi:10.1016/j.apacoust.2017.05.024

Cited by 11 publications

(2 citation statements)

References 11 publications

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“…This system depends upon a pan-tilt-zoom (PTZ) camera that can record human body video. A laser doppler vibrometer (LDV) [26,27] was also used to get audio from a distance by detecting how objects move. The system needed a theodolite to control how LDV is set up.…”

Section: Related Workmentioning

confidence: 99%

Multiple Pedestrian Detection and Tracking in Night Vision Surveillance Systems

Raza¹,

Chelloug²,

Alatiyyah³

et al. 2023

Computers, Materials &Amp; Continua

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Pedestrian detection and tracking are vital elements of today's surveillance systems, which make daily life safe for humans. Thus, human detection and visualization have become essential inventions in the field of computer vision. Hence, developing a surveillance system with multiple object recognition and tracking, especially in low light and night-time, is still challenging. Therefore, we propose a novel system based on machine learning and image processing to provide an efficient surveillance system for pedestrian detection and tracking at night. In particular, we propose a system that tackles a two-fold problem by detecting multiple pedestrians in infrared (IR) images using machine learning and tracking them using particle filters. Moreover, a random forest classifier is adopted for image segmentation to identify pedestrians in an image. The result of detection is investigated by particle filter to solve pedestrian tracking. Through the extensive experiment, our system shows 93% segmentation accuracy using a random forest algorithm that demonstrates high accuracy for background and roof classes. Moreover, the system achieved a detection accuracy of 90% using multiple template matching techniques and 81% accuracy for pedestrian tracking. Furthermore, our system can identify that the detected object is a human. Hence, our system provided the best results compared to the state-ofart systems, which proves the effectiveness of the techniques used for image segmentation, classification, and tracking. The presented method is applicable for human detection/tracking, crowd analysis, and monitoring pedestrians in IR video surveillance.

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Section: Related Workmentioning

confidence: 99%

Multiple Pedestrian Detection and Tracking in Night Vision Surveillance Systems

Raza¹,

Chelloug²,

Alatiyyah³

et al. 2023

Computers, Materials &Amp; Continua

View full text Add to dashboard Cite

show abstract

“…Unfortunately, the energy-based criterion associated with the VAD algorithm is very susceptible to changes in environmental conditions and the method is relatively complex and time-consuming. In an alternative approach, Zhang [25] has proposed using Wiener filtering to attenuate noise outside of the signal bandwidth. However, the application of Wiener filtering to stochastic processes with nonstationary noise produces less than ideal results.…”

Section: Related Workmentioning

confidence: 99%

Highly-Accurate and Real-Time Speech Measurement for Laser Doppler Vibrometers

Wang

Zhang

Zhou

et al. 2022

IEICE Trans. Inf. & Syst.

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Laser Doppler Vibrometers (LDVs) enable the acquisition of remote speech signals by measuring small-scale vibrations around a target. They are now widely used in the fields of information acquisition and national security. However, in remote speech detection, the coherent measurement signal is subject to environmental noise, making detecting and reconstructing speech signals challenging. To improve the detection distance and speech quality, this paper proposes a highly accurate real-time speech measurement method that can reconstruct speech from noisy coherent signals. First, the I/Q demodulation and arctangent phase discrimination are used to extract the phase transformation caused by the acoustic vibration from coherent signals. Then, an innovative smoothness criterion and a novel phase difference-based dynamic bilateral compensation phase unwrapping algorithm are used to remove any ambiguity caused by the arctangent phase discrimination in the previous step. This important innovation results in the highly accurate detection of phase jumps. After this, a further innovation is used to enhance the reconstructed speech by applying an improved waveform-based linear prediction coding method, together with adaptive spectral subtraction. This removes any impulsive or background noise. The accuracy and performance of the proposed method were validated by conducting extensive simulations and comparisons with existing techniques. The results show that the proposed algorithm can significantly improve the measurement of speech and the quality of reconstructed speech signals. The viability of the method was further assessed by undertaking a physical experiment, where LDV equipment was used to measure speech at a distance of 310 m in an outdoor environment. The intelligibility rate for the reconstructed speech exceeded 95%, confirming the effectiveness and superiority of the method for long-distance laser speech measurement.

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Detection of Acoustically Induced Interface Waves Using a Dual-Frequency Sinusoidal Phase Modulating Laser Interferometer and a Normalized PGC-Arctan Demodulation Algorithm

Zhang

Liu

2022

J. Vib. Eng. Technol.

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The novel role of arctangent phase algorithm and voice enhancement techniques in laser hearing

Cited by 11 publications

References 11 publications

Multiple Pedestrian Detection and Tracking in Night Vision Surveillance Systems

Multiple Pedestrian Detection and Tracking in Night Vision Surveillance Systems

Highly-Accurate and Real-Time Speech Measurement for Laser Doppler Vibrometers

Detection of Acoustically Induced Interface Waves Using a Dual-Frequency Sinusoidal Phase Modulating Laser Interferometer and a Normalized PGC-Arctan Demodulation Algorithm

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