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Author (down) Alicia Fornes; Josep Llados; Gemma Sanchez; Xavier Otazu; Horst Bunke edit  doi
openurl 
  Title A Combination of Features for Symbol-Independent Writer Identification in Old Music Scores Type Journal Article
  Year 2010 Publication International Journal on Document Analysis and Recognition Abbreviated Journal IJDAR  
  Volume 13 Issue 4 Pages 243-259  
  Keywords  
  Abstract The aim of writer identification is determining the writer of a piece of handwriting from a set of writers. In this paper, we present an architecture for writer identification in old handwritten music scores. Even though an important amount of music compositions contain handwritten text, the aim of our work is to use only music notation to determine the author. The main contribution is therefore the use of features extracted from graphical alphabets. Our proposal consists in combining the identification results of two different approaches, based on line and textural features. The steps of the ensemble architecture are the following. First of all, the music sheet is preprocessed for removing the staff lines. Then, music lines and texture images are generated for computing line features and textural features. Finally, the classification results are combined for identifying the writer. The proposed method has been tested on a database of old music scores from the seventeenth to nineteenth centuries, achieving a recognition rate of about 92% with 20 writers.  
  Address  
  Corporate Author Thesis  
  Publisher Springer-Verlag Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 1433-2833 ISBN Medium  
  Area Expedition Conference  
  Notes DAG; CAT;CIC Approved no  
  Call Number FLS2010b Serial 1319  
Permanent link to this record
 

 
Author (down) Alicia Fornes; Josep Llados; Gemma Sanchez; Dimosthenis Karatzas edit  doi
openurl 
  Title Rotation Invariant Hand-Drawn Symbol Recognition based on a Dynamic Time Warping Model Type Journal Article
  Year 2010 Publication International Journal on Document Analysis and Recognition Abbreviated Journal IJDAR  
  Volume 13 Issue 3 Pages 229–241  
  Keywords  
  Abstract One of the major difficulties of handwriting symbol recognition is the high variability among symbols because of the different writer styles. In this paper, we introduce a robust approach for describing and recognizing hand-drawn symbols tolerant to these writer style differences. This method, which is invariant to scale and rotation, is based on the dynamic time warping (DTW) algorithm. The symbols are described by vector sequences, a variation of the DTW distance is used for computing the matching distance, and K-Nearest Neighbor is used to classify them. Our approach has been evaluated in two benchmarking scenarios consisting of hand-drawn symbols. Compared with state-of-the-art methods for symbol recognition, our method shows higher tolerance to the irregular deformations induced by hand-drawn strokes.  
  Address  
  Corporate Author Thesis  
  Publisher Springer-Verlag Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 1433-2833 ISBN Medium  
  Area Expedition Conference  
  Notes DAG; IF 2009: 1,213 Approved no  
  Call Number DAG @ dag @ FLS2010a Serial 1288  
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Author (down) Alicia Fornes; Anjan Dutta; Albert Gordo; Josep Llados edit   pdf
doi  openurl
  Title CVC-MUSCIMA: A Ground-Truth of Handwritten Music Score Images for Writer Identification and Staff Removal Type Journal Article
  Year 2012 Publication International Journal on Document Analysis and Recognition Abbreviated Journal IJDAR  
  Volume 15 Issue 3 Pages 243-251  
  Keywords Music scores; Handwritten documents; Writer identification; Staff removal; Performance evaluation; Graphics recognition; Ground truths  
  Abstract 0,405JCR
The analysis of music scores has been an active research field in the last decades. However, there are no publicly available databases of handwritten music scores for the research community. In this paper we present the CVC-MUSCIMA database and ground-truth of handwritten music score images. The dataset consists of 1,000 music sheets written by 50 different musicians. It has been especially designed for writer identification and staff removal tasks. In addition to the description of the dataset, ground-truth, partitioning and evaluation metrics, we also provide some base-line results for easing the comparison between different approaches.
 
  Address  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 1433-2833 ISBN Medium  
  Area Expedition Conference  
  Notes DAG Approved no  
  Call Number Admin @ si @ FDG2012 Serial 2129  
Permanent link to this record
 

 
Author (down) Albert Gordo; Florent Perronnin; Yunchao Gong; Svetlana Lazebnik edit   pdf
doi  openurl
  Title Asymmetric Distances for Binary Embeddings Type Journal Article
  Year 2014 Publication IEEE Transactions on Pattern Analysis and Machine Intelligence Abbreviated Journal TPAMI  
  Volume 36 Issue 1 Pages 33-47  
  Keywords  
  Abstract In large-scale query-by-example retrieval, embedding image signatures in a binary space offers two benefits: data compression and search efficiency. While most embedding algorithms binarize both query and database signatures, it has been noted that this is not strictly a requirement. Indeed, asymmetric schemes which binarize the database signatures but not the query still enjoy the same two benefits but may provide superior accuracy. In this work, we propose two general asymmetric distances which are applicable to a wide variety of embedding techniques including Locality Sensitive Hashing (LSH), Locality Sensitive Binary Codes (LSBC), Spectral Hashing (SH), PCA Embedding (PCAE), PCA Embedding with random rotations (PCAE-RR), and PCA Embedding with iterative quantization (PCAE-ITQ). We experiment on four public benchmarks containing up to 1M images and show that the proposed asymmetric distances consistently lead to large improvements over the symmetric Hamming distance for all binary embedding techniques.  
  Address  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 0162-8828 ISBN Medium  
  Area Expedition Conference  
  Notes DAG; 600.045; 605.203; 600.077 Approved no  
  Call Number Admin @ si @ GPG2014 Serial 2272  
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Author (down) Albert Gordo; Florent Perronnin; Ernest Valveny edit   pdf
url  doi
openurl 
  Title Large-scale document image retrieval and classification with runlength histograms and binary embeddings Type Journal Article
  Year 2013 Publication Pattern Recognition Abbreviated Journal PR  
  Volume 46 Issue 7 Pages 1898-1905  
  Keywords visual document descriptor; compression; large-scale; retrieval; classification  
  Abstract We present a new document image descriptor based on multi-scale runlength
histograms. This descriptor does not rely on layout analysis and can be
computed efficiently. We show how this descriptor can achieve state-of-theart
results on two very different public datasets in classification and retrieval
tasks. Moreover, we show how we can compress and binarize these descriptors
to make them suitable for large-scale applications. We can achieve state-ofthe-
art results in classification using binary descriptors of as few as 16 to 64
bits.
 
  Address  
  Corporate Author Thesis  
  Publisher Elsevier Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 0031-3203 ISBN Medium  
  Area Expedition Conference  
  Notes DAG; 600.042; 600.045; 605.203 Approved no  
  Call Number Admin @ si @ GPV2013 Serial 2306  
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