This paper presents an algorithm to detect and recognize the information contained in road panels. The aim of this work is to complement the functionality of a traffic signposting inspection system based on computer vision, which is able to collect data related to the maintenance state of traffic signs and panels automatically. In this context, not only a good visibility of the panels is vital for a safe use by road users, but also the suitability of the information contained in the traffic panels. The algorithm presented here, which is based on SIFT descriptors to recognize single characters and also on HMMs to recognize whole words, will be able to make an inventory of the information contained in traffic panels with the aim to check its reliability and brevity automatically. Experimental results and conclusions obtained after analysing a diverse set of real images show the effectiveness of the proposed method.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Automatic information recognition of traffic panels using SIFT descriptors and HMMs


    Contributors:
    Gonzalez, A (author) / Bergasa, L M (author) / Yebes, J Javier (author) / Sotelo, M A (author)


    Publication date :

    2010-09-01


    Size :

    938518 byte





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English





    Traffic signs recognition based on PCA-SIFT

    Gao, Hongwei / Liu, Chuanyin / Yu, Yang et al. | IEEE | 2014


    HMMs with Mixtures of Trend Functions for Automatic Speech Recognition

    Deng, L. / Aksmanovic, M. / IEEE; Hong Kong Chapter of Signal Processing | British Library Conference Proceedings | 1994


    PCA-SIFT: A More Distinctive Representation for Local Image Descriptors

    Ke, Y. / Sukthankar, R. / IEEE Computer Society | British Library Conference Proceedings | 2004