Estimating the skew angle in text document images can be a crucial problem in optical character recognition. Based on a new sensor array processing technique, an original solution to skew angle estimation (SAE) is proposed. Thanks to the reformulation of the SAE problem in the framework of angle of arrival theory, a fast and accurate method is presented that is based on the cooperation of two neural networks. The first neural net is a three-layer perceptron receiving on input the values of the correlation matrix of the signals; the output is a "rough" estimation of the angle to estimate. This gross estimate is then used to initialize the weights of a second multi-layer perceptron (MLP). The second MLP is built in order to perform a maximum likelihood-like optimization, therefore reaching good performances. The system, though trained on simulated radar data, shows good performances on noisy handwritten texts.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Cooperation of multi-layer perceptrons for the estimation of skew angle in text document images


    Beteiligte:
    Rondel, N. (Autor:in) / Burel, G. (Autor:in)


    Erscheinungsdatum :

    01.01.1995


    Format / Umfang :

    611526 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    Cooperation of Multi-Layer Perceptrons for the Estimation of Skew Angle in Text Document Images

    Rondel, N. / Burel, G. | British Library Conference Proceedings | 1995


    Automatic Text Skew Estimation in Document Images

    Chen, S. / Haralick, R. M. / Phillips, I. T. | British Library Conference Proceedings | 1995


    Automatic text skew estimation in document images

    Su Chen / Haralick, R.M. / Phillips, I.T. | IEEE | 1995



    An Automatic Algorithm for Text Skew Estimation in Document Images using Recursive Morphological Transforms

    Su, C. / Haralick, R. M. / IEEE; Signal Processing Society | British Library Conference Proceedings | 1994