In this paper an approach to document line segmentation is presented. The algorithm is based on a wavelet transform of the horizontal projective profile of the document image. The projective profile is examined as a one-dimensional discrete signal which is decomposed using the pyramidal wavelet algorithm up to a precise scale, where local minima and maxima are discovered. These local extrema, projected into the input signal, correspond to the spacing between document lines and to the pivots of the lines. The method has been tested on a broad set of printed and handwritten documents and proven to be stable and efficient.
Byzantine neume notation is a specific form of note script, used by the Orthodox Christian Church since ancient times until nowadays for writing music and musical forms in sacred documents. Such documents are an object of extensive scientific research and naturally with the development of computer and information technologies the need of a software tool which can assist these efforts is needed. In this paper a set of algorithms for processing and analysis of Byzantine neume notation are presented which include document image segmentation, character feature vector extraction, classifier learning and character recognition. The described algorithms are implemented as an integrated scientific software system.
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