eprintid: 12080
rev_number: 2
eprint_status: archive
userid: 1
dir: disk0/00/01/20/80
datestamp: 2023-11-10 03:26:37
lastmod: 2023-11-10 03:26:37
status_changed: 2023-11-10 01:16:50
type: article
metadata_visibility: show
creators_name: Subashini, M.M.
creators_name: Deshpande, A.
creators_name: Kannan, R.
title: Study and implementation of various image de-noising methods for traffic sign board recognition
ispublished: pub
note: cited By 0
abstract: The problem of recognizing traffic sign boards in a correct fashion is one of the major challenges since there is an alarming rate of increase in the number of road accidents happening because of incorrect interpretation of traffic sign boards in bad weather conditions. In this paper, a comparative analysis of various noise removal techniques based on calculating different parameters which decide the quality of input roadway symbol like Mean Squared Error (MSE), Peak Signal to Noise Ratio (PSNR) as well as Structural Similarity for measuring Image Quality (SSIM) is being performed and the best technique will be chosen among them which gives minimum Mean Squared Error (MSE) value and maximum Peak Signal to Noise Ratio (PSNR) and Structural Similarity for measuring the Image Quality (SSIM) values. This technique will be quite useful for de-noising a given image which is present in both the testing and the training image databases. © 2019 ASTES Publishers. All rights reserved.
date: 2019
publisher: ASTES Publishers
official_url: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85071357271&doi=10.25046%2faj040466&partnerID=40&md5=307725f921139327d24a2990ef562351
id_number: 10.25046/aj040466
full_text_status: none
publication: Advances in Science, Technology and Engineering Systems
volume: 4
number: 4
pagerange: 545-560
refereed: TRUE
issn: 24156698
citation:   Subashini, M.M. and Deshpande, A. and Kannan, R.  (2019) Study and implementation of various image de-noising methods for traffic sign board recognition.  Advances in Science, Technology and Engineering Systems, 4 (4).  pp. 545-560.  ISSN 24156698