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Angel Sappa and George A. Triantafyllid. 2012. Computer Graphics and Imaging.
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Alicia Fornes and Gemma Sanchez. 2014. Analysis and Recognition of Music Scores. In D. Doermann and K. Tombre, eds. Handbook of Document Image Processing and Recognition. Springer London, 749–774.
Abstract: The analysis and recognition of music scores has attracted the interest of researchers for decades. Optical Music Recognition (OMR) is a classical research field of Document Image Analysis and Recognition (DIAR), whose aim is to extract information from music scores. Music scores contain both graphical and textual information, and for this reason, techniques are closely related to graphics recognition and text recognition. Since music scores use a particular diagrammatic notation that follow the rules of music theory, many approaches make use of context information to guide the recognition and solve ambiguities. This chapter overviews the main Optical Music Recognition (OMR) approaches. Firstly, the different methods are grouped according to the OMR stages, namely, staff removal, music symbol recognition, and syntactical analysis. Secondly, specific approaches for old and handwritten music scores are reviewed. Finally, online approaches and commercial systems are also commented.
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Jose Manuel Alvarez and Antonio Lopez. 2012. Photometric Invariance by Machine Learning. In Theo Gevers, A.G., Joost van de Weijer, Jan-Mark Geusebroek, ed. Color in Computer Vision: Fundamentals and Applications. iConcept Press Ltd, 113–134.
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Angel Sappa, Niki Aifanti, N. Grammalidis and Sotiris Malassiotis. 2004. Advances in Vision-Based Human Body Modeling. In N. Sarris and M. Strintzis., ed. 3D Modeling & Animation: Systhesis and Analysis Techniques for the Human Body.1–26.
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Felipe Lumbreras, Ramon Baldrich, Maria Vanrell, Joan Serrat and Juan J. Villanueva. 1999. Multiresolution texture classification of ceramic tiles. Recent Research developments in optical engineering, Research Signpost, 2: 213–228.
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Ricardo Toledo. 2001. Cardiac workstation and dynamic model to assist in coronary tree analysis. (Ph.D. thesis, .)
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Antonio Lopez. 2000. Multilocal Methods for Ridge and Valley Delineation in Image Analysis. (Ph.D. thesis, .)
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Felipe Lumbreras. 2001. Segmentation, classification and modelization of textures by means of multiresolution decomposition techniques..
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Angel Sappa and Fadi Dornaika. 2006. An Edge-Based Approach to Motion Detection. 6th International Conference on Computational Science (ICCS´06), LNCS 3991:563–570.
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Fadi Dornaika and Angel Sappa. 2006. 3D Face Tracking using Appearance Registration and Robust Iterative Closest Point Algorithm. 21st International Symposium on Computer and Information Sciences (ISCIS´06), LNCS 4263: 532–541.
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