An enhanced vehicle licence plate recognition system based on neural networks (Record no. 6481)

MARC details
000 -LEADER
fixed length control field 01886nam a22001937a 4500
003 - CONTROL NUMBER IDENTIFIER
control field OSt
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20220107122850.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 190617b xxu||||| |||| 00| 0 eng d
040 ## - CATALOGING SOURCE
Transcribing agency IIITMK
100 ## - MAIN ENTRY--PERSONAL NAME
Personal name Deepu K M (93617015)
9 (RLIN) 15792
245 ## - TITLE STATEMENT
Title An enhanced vehicle licence plate recognition system based on neural networks
300 ## - PHYSICAL DESCRIPTION
Extent MSC CS 2017-2019
500 ## - GENERAL NOTE
General note Automatic license plate recognition (ALPR) is an important forensic functionality<br/>for law enforcement and cyber forensics departments for analysing<br/>cctv videos. In many cases number plate image may be blurred or may be of<br/>low resolution due to over speed of vehicles, under adverse atmospheric conditions<br/>or due to low resolution cameras. In this scenario, super-resolution<br/>can be an excellent solution to overcome such limitations. Consecutive frames<br/>in a video may contain dierent information that could be integrated into a<br/>single image, richer in details. Data set required for the project is acquired<br/>through cctv footages and trac monitoring videos. The trained software<br/>model should able to enhance the sequence of frames containing license plates<br/>in low quality real world trac videos captured by closed circuit television<br/>cameras. The ultimate aim of the project is to enhance and recognize low<br/>quality or low resolution blurred images of licence plates from cctv trac<br/>video footages. Image enhancement is implementing using super resolution<br/>of multi frames from videos and recognition part is implementing using optical<br/>character recognition. The scope of project is mainly intended for the<br/>use of law enforcements for detecting the non recognizable images of licence<br/>plates of suspected vehicles.
502 ## - DISSERTATION NOTE
Degree type MSC CS
Name of granting institution 2017-2019
Year degree granted INT
-- Pradeep Kumar K
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element NEURAL NETWORKS
9 (RLIN) 15793
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element AUTOMATIC LICENSE PLATE RECOGNITION
9 (RLIN) 15794
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element DEEP LEARNING
9 (RLIN) 15795
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Source of classification or shelving scheme Dewey Decimal Classification
Koha item type
Holdings
Withdrawn status Lost status Source of classification or shelving scheme Damaged status Not for loan Collection code Home library Current library Shelving location Date acquired Total Checkouts Barcode Date last seen Price effective from Koha item type
    Dewey Decimal Classification     Non Fiction IIITM-K Kerala University of Digital Sciences, Innovation and Technology Knowledge Centre   17/06/2019   R-1485 17/06/2019 17/06/2019 Project Reports