A novel fuzzy approach for shape determination of traffic signs

Document identifier: oai:dalea.du.se:1582
Keyword: Traffic signs, Fuzzy rules, Color segmentation, Out door images
Publication year: 2005
Abstract:

In this paper, a novel fuzzy approach is developed to determine the shape of traffic signs. More than 1600 images of traffic signs were collected in different light conditions by a digital camera mounted in a car and used for testing this approach. Every RGB image was converted into HSV colour space, and segmented by using a set of fuzzy rules depending on the hue and saturation values of each pixel in the HSV colour space. The fuzzy rules are used to extract the colours of the road signs. Objects in each segmented image are labelled and tested for the presence of probable sign. All small objects under certain threshold are discarded, and the remaining objects are tested by a fuzzy shape recognizer which invokes another set of fuzzy rules. Four shape measures are used to decide the shape of the sign; rectangularity, triangularity, ellipticity, and the new shape measure octagonality.

Authors

Hasan Fleyeh

Högskolan Dalarna; Datateknik
Other publications >>

Record metadata

Click to view metadata

	
    header: 
        identifier: oai:dalea.du.se:1582
        datestamp: 2021-04-15T12:08:43Z
        setSpec: SwePub-du
    metadata: 
        mods: 
            @attributes: 
                version: 3.7
            recordInfo: 
                recordContentSource: du
                recordCreationDate: 2005-11-29
            identifier: http://urn.kb.se/resolve?urn=urn:nbn:se:du-1582
            titleInfo: 
                @attributes: 
                    lang: eng
                title: A novel fuzzy approach for shape determination of traffic signs
            abstract: 
In this paper a novel fuzzy approach is developed to determine the shape of traffic signs. More than 1600 images of traffic signs were collected in different light conditions by a digital camera mounted in a car and used for testing this approach. Every RGB image was converted into HSV colour space and segmented by using a set of fuzzy rules depending on the hue and saturation values of each pixel in the HSV colour space. The fuzzy rules are used to extract the colours of the road signs. Objects in each segmented image are labelled and tested for the presence of probable sign. All small objects under certain threshold are discarded and the remaining objects are tested by a fuzzy shape recognizer which invokes another set of fuzzy rules. Four shape measures are used to decide the shape of the sign; rectangularity triangularity ellipticity and the new shape measure octagonality.

            subject: 
                    @attributes: 
                        lang: eng
                    topic: Traffic signs
                    @attributes: 
                        lang: eng
                    topic: Fuzzy rules
                    @attributes: 
                        lang: eng
                    topic: Color segmentation
                    @attributes: 
                        lang: eng
                    topic: out door images
            language: 
                languageTerm: eng
            genre: 
                conference/other
                ref
            note: 
                Published
                1
            name: 
                @attributes: 
                    type: personal
                    authority: du
                namePart: 
                    Fleyeh
                    Hasan
                role: 
                    roleTerm: aut
                affiliation: 
                    Högskolan Dalarna
                    Datateknik
                nameIdentifier: 
                    hfl
                    0000-0002-1429-2345
            originInfo: 
                dateIssued: 2005
                place: 
                    placeTerm: Pune India
            relatedItem: 
                @attributes: 
                    type: host
                titleInfo: 
                    title: Second Indian International Conference on Arificial Intelligence 
            physicalDescription: 
                form: print
            typeOfResource: text