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Wavelet based acoustic detection of moving vehicles Amir Averbuch Valery Zheludev Neta Rabin and Alon Schclar
 

Summary: Wavelet based acoustic detection of moving vehicles
Amir Averbuch Valery Zheludev Neta Rabin and Alon Schclar
School of Computer Science
Tel Aviv University, Tel Aviv 69978, Israel
March 11, 2007
Abstract
We propose a robust algorithm to detect the arrival of a vehicle of arbitrary type when other
noises are present. It is done via analysis of its acoustic signature against an existing database
of recorded and processed acoustic signals. To achieve it with minimum number of false alarms,
we combine a construction of a training database of acoustic signatures signals emitted by
vehicles using the distribution of the energies among blocks of wavelet packet coefficients with
a procedure of random search for a near-optimal footprint (RSNOFP). The number of false
alarms in the detection is minimized even under severe conditions such as: the signals emitted
by vehicles of different types differ from each other, whereas the set of non-vehicle recordings
(the training database) contains signals emitted by planes, helicopters, wind, speech, steps, etc.
The proposed algorithm is robust even when the tested conditions are completely different from
the conditions where the training signals were recorded. The proposed technique has many
algorithmic variations. For example, it can be used to distinguish among different types of
vehicles. The proposed algorithm is a generic solution for process control that is based on a
learning phase (training) followed by an automatic real time detection.

  

Source: Averbuch, Amir - School of Computer Science, Tel Aviv University

 

Collections: Computer Technologies and Information Sciences