@inproceedings{Hankinson_2012b,
 abstract = {Optical music recognition (OMR) and optical character recognition (OCR) have traditionally been used for document transcription–that is, extracting text or symbolic music from page images for use in an editor while discarding all spatial relationships between the transcribed notation and the original image. In this paper we discuss how OCR has shifted fundamentally from a transcription tool to an indexing tool for document image collections resulting from large digitization efforts. OMR tools and procedures, in contrast, are still focused on small-scale modes of operation. We argue that a shift in OMR development towards document image indexing would present new opportunities for searching, browsing, and analyzing large musical document collections. We present a prototype system we built to evaluate the tools and to develop practices needed to process print and manuscript sources.},
 author = {Hankinson, Andrew and Burgoyne, John Ashley and Vigliensoni, Gabriel and Porter, Alastair and Thompson, Jessica and Liu, Wendy and Chiu, Remi and Fujinaga, Ichiro},
 title = {Digital Document Image Retrieval Using Optical Music Recognition},
 url = {http://ismir2012.ismir.net/event/papers/577_ISMIR_2012.pdf},
 pages = {577–582},
 publisher = {{FEUP Edi{\c{c}}{\~o}es}},
 isbn = {978-972-752-144-9},
 editor = {Gouyon, Fabien and Herrera, Perfecto and Martins, Luis Gustavo and M{\"u}ller, Meinard},
 booktitle = {Proceedings of the 13th International Society for Music Information Retrieval Conference, ISMIR 2012, Mosteiro S.Bento Da Vit{\'o}ria, Porto, Portugal, October 8-12, 2012},
 year = {2012}
}

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We argue that a shift in OMR development towards document image indexing would present new opportunities for searching, browsing, and analyzing large musical document collections. We present a prototype system we built to evaluate the tools and to develop practices needed to process print and manuscript sources.","author":[{"propositions":[],"lastnames":["Hankinson"],"firstnames":["Andrew"],"suffixes":[]},{"propositions":[],"lastnames":["Burgoyne"],"firstnames":["John","Ashley"],"suffixes":[]},{"propositions":[],"lastnames":["Vigliensoni"],"firstnames":["Gabriel"],"suffixes":[]},{"propositions":[],"lastnames":["Porter"],"firstnames":["Alastair"],"suffixes":[]},{"propositions":[],"lastnames":["Thompson"],"firstnames":["Jessica"],"suffixes":[]},{"propositions":[],"lastnames":["Liu"],"firstnames":["Wendy"],"suffixes":[]},{"propositions":[],"lastnames":["Chiu"],"firstnames":["Remi"],"suffixes":[]},{"propositions":[],"lastnames":["Fujinaga"],"firstnames":["Ichiro"],"suffixes":[]}],"title":"Digital Document Image Retrieval Using Optical Music Recognition","url":"http://ismir2012.ismir.net/event/papers/577_ISMIR_2012.pdf","pages":"577–582","publisher":"FEUP Edições","isbn":"978-972-752-144-9","editor":[{"propositions":[],"lastnames":["Gouyon"],"firstnames":["Fabien"],"suffixes":[]},{"propositions":[],"lastnames":["Herrera"],"firstnames":["Perfecto"],"suffixes":[]},{"propositions":[],"lastnames":["Martins"],"firstnames":["Luis","Gustavo"],"suffixes":[]},{"propositions":[],"lastnames":["Müller"],"firstnames":["Meinard"],"suffixes":[]}],"booktitle":"Proceedings of the 13th International Society for Music Information Retrieval Conference, ISMIR 2012, Mosteiro S.Bento Da Vitória, Porto, Portugal, October 8-12, 2012","year":"2012","bibtex":"@inproceedings{Hankinson_2012b,\n abstract = {Optical music recognition (OMR) and optical character recognition (OCR) have traditionally been used for document transcription–that is, extracting text or symbolic music from page images for use in an editor while discarding all spatial relationships between the transcribed notation and the original image. In this paper we discuss how OCR has shifted fundamentally from a transcription tool to an indexing tool for document image collections resulting from large digitization efforts. OMR tools and procedures, in contrast, are still focused on small-scale modes of operation. We argue that a shift in OMR development towards document image indexing would present new opportunities for searching, browsing, and analyzing large musical document collections. We present a prototype system we built to evaluate the tools and to develop practices needed to process print and manuscript sources.},\n author = {Hankinson, Andrew and Burgoyne, John Ashley and Vigliensoni, Gabriel and Porter, Alastair and Thompson, Jessica and Liu, Wendy and Chiu, Remi and Fujinaga, Ichiro},\n title = {Digital Document Image Retrieval Using Optical Music Recognition},\n url = {http://ismir2012.ismir.net/event/papers/577_ISMIR_2012.pdf},\n pages = {577–582},\n publisher = {{FEUP Edi{\\c{c}}{\\~o}es}},\n isbn = {978-972-752-144-9},\n editor = {Gouyon, Fabien and Herrera, Perfecto and Martins, Luis Gustavo and M{\\\"u}ller, Meinard},\n booktitle = {Proceedings of the 13th International Society for Music Information Retrieval Conference, ISMIR 2012, Mosteiro S.Bento Da Vit{\\'o}ria, Porto, Portugal, October 8-12, 2012},\n year = {2012}\n}\n\n\n","author_short":["Hankinson, A.","Burgoyne, J. 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