Hand-drawn symbol recognition in graphic documents using deformable template matching and a bayesian framework

Ernest Valveny, Enric Martí

    Research output: Contribution to journalArticleResearchpeer-review

    6 Citations (Scopus)

    Abstract

    Hand-drawn symbols can take many different and distorted shapes from their ideal representation. Then, very flexible methods are needed to be able to handle unconstrained drawings. We propose here to extend our previous work in hand-drawn symbol recognition based on a bayesian framework and deformable template matching. This approach gets flexibility enough to fit distorted shapes in the drawing while keeping fidelity to the ideal shape of the symbol. In this work we define the similarity measure between an image and a symbol based on the distance from every pixel in the image to the lines in the symbol. Matching is carried out using an implementation of the EM algorithm. Thus, we can improve recognition rates and computation time with respect to our previous formulation based on a simulated annealing algorithm. © 2000 IEEE.
    Original languageEnglish
    Pages (from-to)239-242
    JournalProceedings - International Conference on Pattern Recognition
    Volume15
    Issue number2
    Publication statusPublished - 1 Dec 2000

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