000			01886nam a22001937a 4500
003			OSt
005			20220107122850.0
008			190617b xxu||||| |||| 00| 0 eng d
040			_cIIITMK
100			_aDeepu K M (93617015) _915792
245			_aAn enhanced vehicle licence plate recognition system based on neural networks
300			_aMSC CS 2017-2019
500			_aAutomatic license plate recognition (ALPR) is an important forensic functionality for law enforcement and cyber forensics departments for analysing cctv videos. In many cases number plate image may be blurred or may be of low resolution due to over speed of vehicles, under adverse atmospheric conditions or due to low resolution cameras. In this scenario, super-resolution can be an excellent solution to overcome such limitations. Consecutive frames in a video may contain dierent information that could be integrated into a single image, richer in details. Data set required for the project is acquired through cctv footages and trac monitoring videos. The trained software model should able to enhance the sequence of frames containing license plates in low quality real world trac videos captured by closed circuit television cameras. The ultimate aim of the project is to enhance and recognize low quality or low resolution blurred images of licence plates from cctv trac video footages. Image enhancement is implementing using super resolution of multi frames from videos and recognition part is implementing using optical character recognition. The scope of project is mainly intended for the use of law enforcements for detecting the non recognizable images of licence plates of suspected vehicles.
502			_bMSC CS _c 2017-2019 _dINT _ePradeep Kumar K
650			_aNEURAL NETWORKS _915793
650			_aAUTOMATIC LICENSE PLATE RECOGNITION _915794
650			_aDEEP LEARNING _915795
942			_2ddc _cPR
999			_c6481 _d6481