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    <name>Article</name>
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              <text>Identification of ambulance in traffic videos using image processing techniques</text>
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              <text>Color space thresholding; Multilevel thresholding; Optical Character Recognition (OCR); Region matching for text detection</text>
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              <text>Traffic congestion is one of the commonly faced problems in the Urban areas. To eliminate these problems, there is a need for an Intelligent Transportation System (ITS) that proposes an efficient method to reduce the traffic problems and introduces the priority system for the Emergency vehicles. This paper proposes two frameworks that identify ambulance in traffic videos based on features such as color, siren and text. Frames are extracted from videos to employ methods like multilevel thresholding and region matching. Multilevel thresholding is used for segmenting the ambulance from the other occurring vehicles based on the white color. Region matching for text detection method is employed in the segmented vehicle. Color space thresholding is used for the detection of siren based on red or blue color feature. Optical character recognition (OCR) is employed to extract the text in the frame. Word comparison and Matching detects the ambulance text based on the outcome of OCR. The performance of Framework 1 and Framework 2 are evaluated based on Word accuracy and from the experimental results it is observed that Framework 2 is better from 75% word accuracy.  2018, Institute of Advanced Scientific Research, Inc. All Rights reserved.</text>
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              <text>Karthik Raj P.R.; Praveen Kumar P.U.</text>
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              <text>Journal of Advanced Research in Dynamical and Control Systems, Vol-10, pp. 213-224.</text>
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              <text>Institute of Advanced Scientific Research, Inc.</text>
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              <text>2018-01-01</text>
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              <text>ISSN: 1943023X</text>
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              <text>Online</text>
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              <text>English</text>
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              <text>Karthik Raj P.R., Department of Computer Science, Christ University, Bengaluru, India; Praveen Kumar P.U., Department of Computer Science, Christ University, Bengaluru, India</text>
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