Vehicle Detection and Recognition is a challenging move in the field of Traffic Management as it requires special attention and technique for the efficient management of vehicles. Vehicle Recognition and classification is a critical application of Intelligent Transport System (ITS). It is a process of identifying the moving vehicle on the road to analyze the flow rate and then accurately classify different objects. Lately, building an automatic onboard driver assistance system to assist drivers about possible collisions and clashes has received immense significance. Many researchers have proposed different methodologies using different source inputs to detect day and night vision vehicles. However, vehicle detection at night is an uphill task. It involves testing of classification algorithm under various factors such as Rainy weather, Snowy weather, Low illumination, etc., due to which identification of vehicle becomes a difficult task. This paper presents a comprehensive panorama of the work done so far by the researchers in vehicle detection day and night time. Various vehicle detection methods are discussed, along with the role of ITS in the application of vehicle detection and recognition. Also, it provides a concise review of the reported methods used for recognizing different types of vehicles in different environments and challenges faced by other researchers in their research area.
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Hong Kong Polytech Univ, Dept Logist & Maritime Studies, Hong Kong, Peoples R ChinaHong Kong Polytech Univ, Dept Logist & Maritime Studies, Hong Kong, Peoples R China
Yang, Dong
Wu, Lingxiao
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Hong Kong Polytech Univ, Dept Logist & Maritime Studies, Hong Kong, Peoples R ChinaHong Kong Polytech Univ, Dept Logist & Maritime Studies, Hong Kong, Peoples R China
Wu, Lingxiao
Wang, Shuaian
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Hong Kong Polytech Univ, Dept Logist & Maritime Studies, Hong Kong, Peoples R ChinaHong Kong Polytech Univ, Dept Logist & Maritime Studies, Hong Kong, Peoples R China
Wang, Shuaian
Jia, Haiying
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Norwegian Sch Econ, Ctr Appl Res NHH, Bergen, NorwayHong Kong Polytech Univ, Dept Logist & Maritime Studies, Hong Kong, Peoples R China
Jia, Haiying
Li, Kevin X.
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Chung Ang Univ, Dept Int Logist, Seoul, South KoreaHong Kong Polytech Univ, Dept Logist & Maritime Studies, Hong Kong, Peoples R China