xiao chen

This paper presents a road vehicle recognition and classification approach for intelligent transportation systems. This approach uses a roadside installed low cost magnetometer and associated data collection system. The system measures the magnetic field changing, detects passing vehicles and recognizes vehicle types. We introduce Mel Frequency Cepstral Coefficients (MFCC) to analyze vehicle magnetic signals and extract it as vehicle feature with the representation of cepstrum, frame energy, and gap cepstrum of magnetic signals.