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Building Road-Sign Classifiers Using a Trainable Similarity Measure

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985556%3A_____%2F06%3A00041079" target="_blank" >RIV/67985556:_____/06:00041079 - isvavai.cz</a>

  • Alternative codes found

    RIV/61384399:31160/06:00025099

  • Result on the web

  • DOI - Digital Object Identifier

Alternative languages

  • Result language

    angličtina

  • Original language name

    Building Road-Sign Classifiers Using a Trainable Similarity Measure

  • Original language description

    A frequently used strategy for road sign classification is based on the normalized cross-correlation similarity to class prototypes followed by the nearest neighbor classifier. Because of the global nature of the cross-correlation similarity, this methodsuffers from presence of uninformative pixels (caused e.g. by occlusions), and is computationally demanding. In this paper, a novel concept of a trainable similarity measure is introduced which alleviates these shortcomings. The similarity is based on individual matches in a set of local image regions. The set of regions, relevant for a particular similarity assessment, is refined by the training process. It is illustrated on a set of experiments with road sign classification problems that the trainable similarity yields high-performance data representations and classifiers. Apart from a multi-class classification accuracy, also non-sign rejection capability, and computational demands in execution are discussed. It appears that the tra

  • Czech name

    Klasifikace dopravních značek založená na míře podobnosti zkoumaného objektu k třídě reprezentované typickou značkou

  • Czech description

    Návrh klasifikátoru dopravních značek založeného na podobnosti zkoumaného objektu ke třídě značek reprezentované vždy typickou značkou (prototype-based rule). Navržen algoritmus založený na trénování podle množiny prototypů (trainable similarity). Experimenty na několika datových souborech ilustrují vyšší účinnost klasifikátoru v porovnání s klasifikátory až dosud používanými pro klasifikaci značek. Byly testovány i další vlastnosti navrženého klasifikátoru jako robustnost a časová náročnost.

Classification

  • Type

    J<sub>x</sub> - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)

  • CEP classification

    BB - Applied statistics, operational research

  • OECD FORD branch

Result continuities

  • Project

    Result was created during the realization of more than one project. More information in the Projects tab.

  • Continuities

    P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>Z - Vyzkumny zamer (s odkazem do CEZ)

Others

  • Publication year

    2006

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Name of the periodical

    IEEE Transactions on Intelligent Transportation Systems

  • ISSN

    1524-9050

  • e-ISSN

  • Volume of the periodical

    7

  • Issue of the periodical within the volume

    3

  • Country of publishing house

    US - UNITED STATES

  • Number of pages

    13

  • Pages from-to

    309-321

  • UT code for WoS article

  • EID of the result in the Scopus database