Object Tracking, Shadow Removal and Collision Event Detection for Traffic Surveillance System

• Main Authors: Fu-Lin Chang, 張馥麟
• Other Authors: Shen-Chuan Tai
• Format: Others
• Language: en_US
• Published: 2006
• Online Access: http://ndltd.ncl.edu.tw/handle/79858593116661730622

碩士 === 國立成功大學 === 電腦與通信工程研究所 === 94 === 　　In　recent　years,　public　safety　becomes　more　and　more　important　issue　in　our　daily　life.　In　order　to　reduce　the　damage　from　traffic　incident,　video-based　surveillance　system　has　a　wide　range　of　applications　for　traffic　monitoring.　In　this　thesis,　an　automatic　traffic　surveillance　system　is　presented　to　track　moving　objects　and　detect　the　collision　event.　First,　initial　background　model　is　built　to　extract　the　foreground　regions　by　background　subtraction　and　background　model　must　be　updated　by　the　result　of　extracted　foreground　region　due　to　illumination　change　of　sunlight.　Next,　self-shadows　are　removed　based　on　the　information　of　brightness　and　chromaticity　distortions　between　foreground　and　background　pixels.　Then,　centroid　matching　strategy　is　used　to　find　out　the　correspondence　of　regions　in　the　successive　frames,　and　the　system　not　only　can　track　individual　moving　objects,　but　also　can　discriminate　the　mergence　and　split.　Final,　the　system　can　detect　the　collision　event　and　troublemaker　fleeing　from　traffic　incident　by　proposed　method.