Research And Application Of Support Vector Machine Based Vehicle Monitoring Technology

With the rapid progress and development of urban transportation system and modern information technology, Intelligent Transportation System (ITS) was born. Currently, ITS is of highly information and technology, including geography information system, global positioning system, vehicle automatical recognition system, vehicle collisition dectection system, automatical driving system, multi-media communication system, etc. It covers many aspects and is full of technology with brilliant research and market future.This article mainly focus on vehicle monitoring like license plate recognition, vehicle type recognition of ITS. According to support vector machine theory, upon current algorithm, A new algorithm of image classification and recognition is put forwarded, which can be applied in real condition. This algorithm is effective and self-adaptive, giving high rate of recognition basing on minor data learning.Support Vector Machine is a new machine learning algorithm proposed by V.Vapnik and his group at AT&T Bell laboratory for classification and regression question. It based on structural risk minimization can effectively solve the over study problem and has the good extension and the better classified accuracy. It has become the new research hotspot after the research of pattern recognition and artificial nerve net and will push the development in machine learning theory and technology.Recently, Support Vector Machine is well applied in pattern recognition, function approximate, data mining and text auto categorization. Traditional Support Vector Machine is developed for binary classification problems, while for practical problems such as data mining and text categorization that need to deal with huge and mufti-category data. It is one of the important challenges how to solve large scale and mufti-class problemes in recent years.