Road and traffic sign detection and recognition

Document identifier: oai:dalea.du.se:1426
Keyword: Traffic signs, Sign detection, Sign recognition
Publication year: 2005
Relevant Sustainable Development Goals (SDGs):

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Abstract:

This paper presents an overview of the road and traffic sign detection and recognition. It describes the characteristics of the road signs, the requirements and difficulties behind road signs detection and recognition, how to deal with outdoor images, and the different techniques used in the image segmentation based on the colour analysis, shape analysis. It shows also the techniques used for the recognition and classification of the road signs. Although image processing plays a central role in the road signs recognition, especially in colour analysis, but the paper points to many problems regarding the stability of the received information of colours, variations of these colours with respect to the daylight conditions, and absence of a colour model that can led to a good solution. This means that there is a lot of work to be done in the field, and a lot of improvement can be achieved. Neural networks were widely used in the detection and the recognition of the road signs. The majority of the authors used neural networks as a recognizer, and as classifier. Some other techniques such as template matching or classical classifiers were also used. New techniques should be involved to increase the robustness, and to get faster systems for real-time applications.

Authors

Hasan Fleyeh

Högskolan Dalarna; Datateknik
Other publications >>

Mark Dougherty

Högskolan Dalarna; Datateknik
Other publications >>

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    header: 
        identifier: oai:dalea.du.se:1426
        datestamp: 2021-04-15T12:05:57Z
        setSpec: SwePub-du
    metadata: 
        mods: 
            @attributes: 
                version: 3.7
            recordInfo: 
                recordContentSource: du
                recordCreationDate: 2005-08-27
            identifier: http://urn.kb.se/resolve?urn=urn:nbn:se:du-1426
            titleInfo: 
                @attributes: 
                    lang: eng
                title: Road and traffic sign detection and recognition
            abstract: 
This paper presents an overview of the road and traffic sign detection and recognition. It describes the characteristics of the road signs the requirements and difficulties behind road signs detection and recognition how to deal with outdoor images and the different techniques used in the image segmentation based on the colour analysis shape analysis. It shows also the techniques used for the recognition and classification of the road signs. Although image processing plays a central role in the road signs recognition especially in colour analysis but the paper points to many problems regarding the stability of the received information of colours variations of these colours with respect to the daylight conditions and absence of a colour model that can led to a good solution. This means that there is a lot of work to be done in the field and a lot of improvement can be achieved. Neural networks were widely used in the detection and the recognition of the road signs. The majority of the authors used neural networks as a recognizer and as classifier. Some other techniques such as template matching or classical classifiers were also used. New techniques should be involved to increase the robustness and to get faster systems for real-time applications.

            subject: 
                    @attributes: 
                        lang: eng
                    topic: Traffic signs
                    @attributes: 
                        lang: eng
                    topic: sign detection
                    @attributes: 
                        lang: eng
                    topic: sign recognition
            language: 
                languageTerm: eng
            genre: 
                conference/other
                ref
            note: 
                Published
                2
            name: 
                    @attributes: 
                        type: personal
                        authority: du
                    namePart: 
                        Fleyeh
                        Hasan
                    role: 
                        roleTerm: aut
                    affiliation: 
                        Högskolan Dalarna
                        Datateknik
                    nameIdentifier: 
                        hfl
                        0000-0002-1429-2345
                    @attributes: 
                        type: personal
                        authority: du
                    namePart: 
                        Dougherty
                        Mark
                    role: 
                        roleTerm: aut
                    affiliation: 
                        Högskolan Dalarna
                        Datateknik
                    nameIdentifier: mdo
            originInfo: 
                dateIssued: 2005
                place: 
                    placeTerm: Poznan Poland
            relatedItem: 
                @attributes: 
                    type: host
                titleInfo: 
                    title: 10th EWGT Meeting and 16th Mini-EURO Conference 
            physicalDescription: 
                form: print
            typeOfResource: text