Optical Music Recognition Ichiro Fujinaga McGill University 2003

Content Optical Music Recognition Levy Project Gamera Levy Sheet Music Collection Digital Workflow Management Gamera Guido / NoteAbility

Optical Music Recognition (OMR) Trainable open-source OMR system in development since 1984 Staff recognition and removal Run-length coding Projections Lyric removal / classifier Stems and notehead removal Music symbol classifier Score reconstruction Demo

OMR: Classifier Connected-component analysis Feature extraction, e.g: Width, height, aspect ratio Number of holes Central moments k-nearest neighbor classifier Genetic algorithm

Overall Architecture for OMR Image File Staff removal Segmentation Recognition K-NN Classifier Output Symbol Name Optimization Genetic Algorithm K-nn Classifier Knowledge Base Feature Vectors Best Weight Vector Off-line

Lester S. Levy Collection

Lester S. Levy Collection North American sheet music (1780–1960) Digitized 29,000 pieces including “The Star-Spangle Banner” and “Yankee Doodle” Database of: text index records images of music (8bit gray) lyrics (first lines of verse and chorus) color images of cover sheets (32bit) http://levysheetmusic.mse.jhu.edu

Digital Workflow Management Reduce the manual intervention for large-scale digitization projects Creation of data repository (text, image, sound) Optical Music Recognition (OMR) Gamera XML-based metadata composer, lyricist, arranger, performer, artist, engraver, lithographer, dedicatee, and publisher cross-references for various forms of names, pseudonyms authoritative versions of names and subject terms Music and lyric search engines Analysis toolkit

The problem Suitable OCR for lyrics not found Commercial OCR systems are often inadequate for non-standard documents The market for specialized recognition of historical documents is very small Researchers performing document recognition often “re-invent” the basic image processing wheel

The solution Provide easy to use tools to allow domain experts (people with specialized knowledge of a collection) to create custom recognition applications Generalize OMR for structured documents

Introducing Gamera Framework for creation of structured document recognition system Designed for domain experts Image processing tools (filters, binarizations, etc.) Document segmentation and analysis Symbol segmentation and classification Feature extraction and selection Classifier selection and combiners Syntactical and semantic analysis Generalized Algorithms and Methods for Enhancement and Restoration of Archives

Features of Gamera Portability (Unix, Windows, Mac) Extensibility (Python and C++ plugins) Easy-to-use (experts and programmers) Open source Graphic User Interface Interactive / Batchable (scripts)

Architecture of Gamera Graphic User Interface (wxWindows) Scripting Environment (Python) Plugins (Python) Automatic Plugin Wrapper (Boost) Plugins (C++) GAMERA Core (C++)

Example of C++ Plugin // Number of pixels in matrix #include “gamera.hh” #ifdef __area_wrap__ #define NARGS 1 #define ARG1_ONEBIT #endif using namespace Gamera; template <class T> feature_t area(T &m) { return feature_t(m.nrows() * m.ncols()); }

Example of Python Plugin // This filters a list of CC objects import gamera def filter_wide(ccs, max_width): tmp = [] for x in ccs: if x.ncols() > max_width: x.fill_matrix(0) else: tmp.append(x) return tmp

Gamera: Interface (screenshot in Linux)

Gamera: Interface (screenshot in Linux)

Histogram (screenshot in Linux)

Thresholding (screenshot in Linux)

Thresholding (screenshot in Linux)

Staff removal: Lute tablature

Classifier: Lute (screenshot in Linux)

Staff removal: Neums

Classifier: Neums (screenshot in Linux)

Greek example

GUIDO Music Notation Format H. Hoos, K. Renz, J. Kilian “A formal language for score-level representation” Plain text: readable, platform independent Extensible and flexible Adequate representation NoteServer: Web/Windows GUIDO/XML NoteAbility (K. Hamel)

GUIDO: An example { [ \beamsOff | \clef<"treble"> \key<"D"> f#*1/8. g*1/16 | a*1/4. d2*1/8 d*1/4. c#*1/8 | e1*1/2 _*1/4 f#*1/8. g*1/16 | c#2*1/4. b1*1/8 a*1/4. g*1/8 | | e#*1/2 f#*1/4 f#*1/8. g*1/16 | e1*1/2 _*1/4 f#*1/8 g | c#2*1/4. b1*1/8 a*1/4. c#*1/8 ], …

NoteAbility Demo

Conclusions Gamera allows rapid development of domain-specific document recognition applications Domain experts can customize and control all aspects of the recognition process Includes an easy-to-use interactive environment for experimentation Beta version available on Linux OS X version in preparation

Projections X-projections Y-projections back