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Author |
Alicia Fornes; Anjan Dutta; Albert Gordo; Josep Llados |


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Title |
CVC-MUSCIMA: A Ground-Truth of Handwritten Music Score Images for Writer Identification and Staff Removal |
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Journal Article |
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Year |
2012 |
Publication |
International Journal on Document Analysis and Recognition |
Abbreviated Journal |
IJDAR |
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Volume |
15 |
Issue |
3 |
Pages  |
243-251 |
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Keywords |
Music scores; Handwritten documents; Writer identification; Staff removal; Performance evaluation; Graphics recognition; Ground truths |
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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. |
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1433-2833 |
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DAG |
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no |
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Admin @ si @ FDG2012 |
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2129 |
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Author |
Sanket Biswas; Pau Riba; Josep Llados; Umapada Pal |


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Title |
Beyond Document Object Detection: Instance-Level Segmentation of Complex Layouts |
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Journal Article |
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Year |
2021 |
Publication |
International Journal on Document Analysis and Recognition |
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IJDAR |
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24 |
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269–281 |
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Information extraction is a fundamental task of many business intelligence services that entail massive document processing. Understanding a document page structure in terms of its layout provides contextual support which is helpful in the semantic interpretation of the document terms. In this paper, inspired by the progress of deep learning methodologies applied to the task of object recognition, we transfer these models to the specific case of document object detection, reformulating the traditional problem of document layout analysis. Moreover, we importantly contribute to prior arts by defining the task of instance segmentation on the document image domain. An instance segmentation paradigm is especially important in complex layouts whose contents should interact for the proper rendering of the page, i.e., the proper text wrapping around an image. Finally, we provide an extensive evaluation, both qualitative and quantitative, that demonstrates the superior performance of the proposed methodology over the current state of the art. |
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DAG; 600.121; 600.140; 110.312 |
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Admin @ si @ BRL2021b |
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3574 |
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Author |
David Fernandez; Josep Llados; Alicia Fornes |

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Title |
A graph-based approach for segmenting touching lines in historical handwritten documents |
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Journal Article |
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2014 |
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International Journal on Document Analysis and Recognition |
Abbreviated Journal |
IJDAR |
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17 |
Issue |
3 |
Pages  |
293-312 |
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Text line segmentation; Handwritten documents; Document image processing; Historical document analysis |
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Abstract |
Text line segmentation in handwritten documents is an important task in the recognition of historical documents. Handwritten document images contain text lines with multiple orientations, touching and overlapping characters between consecutive text lines and different document structures, making line segmentation a difficult task. In this paper, we present a new approach for handwritten text line segmentation solving the problems of touching components, curvilinear text lines and horizontally overlapping components. The proposed algorithm formulates line segmentation as finding the central path in the area between two consecutive lines. This is solved as a graph traversal problem. A graph is constructed using the skeleton of the image. Then, a path-finding algorithm is used to find the optimum path between text lines. The proposed algorithm has been evaluated on a comprehensive dataset consisting of five databases: ICDAR2009, ICDAR2013, UMD, the George Washington and the Barcelona Marriages Database. The proposed method outperforms the state-of-the-art considering the different types and difficulties of the benchmarking data. |
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Springer Berlin Heidelberg |
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1433-2833 |
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DAG; 600.056; 600.061; 602.006; 600.077 |
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Admin @ si @ FLF2014 |
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2459 |
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Author |
Kaida Xiao; Sophie Wuerger; Chenyang Fu; Dimosthenis Karatzas |

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Title |
Unique Hue Data for Colour Appearance Models. Part i: Loci of Unique Hues and Hue Uniformity |
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Journal Article |
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2011 |
Publication |
Color Research & Application |
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CRA |
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36 |
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5 |
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316-323 |
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unique hues; colour appearance models; CIECAM02; hue uniformity |
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Psychophysical experiments were conducted to assess unique hues on a CRT display for a large sample of colour-normal observers (n 1⁄4 185). These data were then used to evaluate the most commonly used colour appear- ance model, CIECAM02, by transforming the CIEXYZ tris- timulus values of the unique hues to the CIECAM02 colour appearance attributes, lightness, chroma and hue angle. We report two findings: (1) the hue angles derived from our unique hue data are inconsistent with the commonly used Natural Color System hues that are incorporated in the CIECAM02 model. We argue that our predicted unique hue angles (derived from our large dataset) provide a more reliable standard for colour management applications when the precise specification of these salient colours is im- portant. (2) We test hue uniformity for CIECAM02 in all four unique hues and show significant disagreements for all hues, except for unique red which seems to be invariant under lightness changes. Our dataset is useful to improve the CIECAM02 model as it provides reliable data for benchmarking. |
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Wiley Periodicals Inc |
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Admin @ si @ XWF2011 |
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1816 |
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Author |
Marçal Rusiñol; Josep Llados; Gemma Sanchez |

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Title |
Symbol Spotting in Vectorized Technical Drawings Through a Lookup Table of Region Strings |
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Journal Article |
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Year |
2010 |
Publication |
Pattern Analysis and Applications |
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PAA |
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13 |
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3 |
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321-331 |
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In this paper, we address the problem of symbol spotting in technical document images applied to scanned and vectorized line drawings. Like any information spotting architecture, our approach has two components. First, symbols are decomposed in primitives which are compactly represented and second a primitive indexing structure aims to efficiently retrieve similar primitives. Primitives are encoded in terms of attributed strings representing closed regions. Similar strings are clustered in a lookup table so that the set median strings act as indexing keys. A voting scheme formulates hypothesis in certain locations of the line drawing image where there is a high presence of regions similar to the queried ones, and therefore, a high probability to find the queried graphical symbol. The proposed approach is illustrated in a framework consisting in spotting furniture symbols in architectural drawings. It has been proved to work even in the presence of noise and distortion introduced by the scanning and raster-to-vector processes. |
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Springer-Verlag |
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1433-7541 |
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DAG @ dag @ RLS2010 |
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1165 |
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