Hardware accelerated implementation of wavelet transform for machine vision in road traffic monitoring system

A system for road traffic monitoring has been described. This machine vision system is using small and cheap camera and FPGA postprocessor with wireless network interface. Power for the system will be delivered from solar panels and therefore the system is optimized to be power efficient. In this paper the machine vision traffic jam detection module based on wavelet transform is described. This module correctly detects and measures traffic jams or very slow traffic conditions when background subtraction algorithms (used for vehicle counting) are not suitable. Optical flow algorithms can also be used but they are computationally expensive. Sample discrete wavelet transform based algorithm and its hardware implementation in FPGA are examined in the paper. Hardware accelerated discrete wavelet transform can be also applied to image compression when image has to be transferred to the traffic control center (picture quality and frame rate depends on wireless network quality). Results of sample traffic classification are presented and compared. This work has been supported by the Polish Ministry of Science and Higher Education under R&D grant no. R02 014 01 from the Science Budget 2007-2008.