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Anjan Dutta; Josep Llados; Umapada Pal |


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Title |
Bag-of-GraphPaths Descriptors for Symbol Recognition and Spotting in Line Drawings |
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2011 |
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In proceedings of 9th IAPR Workshop on Graphic Recognition |
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Graphical symbol recognition and spotting recently have become an important research activity. In this work we present a descriptor for symbols, especially for line drawings. The descriptor is based on the graph representation of graphical objects. We construct graphs from the vectorized information of the binarized images, where the critical points detected by the vectorization algorithm are considered as nodes and the lines joining them are considered as edges. Graph paths between two nodes in a graph are the finite sequences of nodes following the order from the starting to the final node. The occurrences of different graph paths in a given graph is an important feature, as they capture the geometrical and structural attributes of a graph. So the graph representing a symbol can efficiently be represent by the occurrences of its different paths. Their occurrences in a symbol can be obtained in terms of a histogram counting the number of some fixed prototype paths, we call the histogram as the Bag-of-GraphPaths (BOGP). These BOGP histograms are used as a descriptor to measure the distance among the symbols in vector space. We use the descriptor for three applications, they are: (1) classification of the graphical symbols, (2) spotting of the architectural symbols on floorplans, (3) classification of the historical handwritten words. |
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Seoul, Korea |
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Springer Berlin Heidelberg |
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0302-9743 |
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978-3-642-36823-3 |
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GREC |
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Admin @ si @ DLP2011c |
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1825 |
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Author |
Sophie Wuerger; Kaida Xiao; Chenyang Fu; Dimosthenis Karatzas |

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Title |
Colour-opponent mechanisms are not affected by age-related chromatic sensitivity changes |
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Journal Article |
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2010 |
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Ophthalmic and Physiological Optics |
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OPO |
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30 |
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5 |
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635-659 |
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The purpose of this study was to assess whether age-related chromatic sensitivity changes are associated with corresponding changes in hue perception in a large sample of colour-normal observers over a wide age range (n = 185; age range: 18-75 years). In these observers we determined both the sensitivity along the protan, deutan and tritan line; and settings for the four unique hues, from which the characteristics of the higher-order colour mechanisms can be derived. We found a significant decrease in chromatic sensitivity due to ageing, in particular along the tritan line. From the unique hue settings we derived the cone weightings associated with the colour mechanisms that are at equilibrium for the four unique hues. We found that the relative cone weightings (w(L) /w(M) and w(L) /w(S)) associated with the unique hues were independent of age. Our results are consistent with previous findings that the unique hues are rather constant with age while chromatic sensitivity declines. They also provide evidence in favour of the hypothesis that higher-order colour mechanisms are equipped with flexible cone weightings, as opposed to fixed weights. The mechanism underlying this compensation is still poorly understood. |
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DAG; IF: 1.259 |
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Admin @ si @ WXF2010 |
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1826 |
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Author |
Alicia Fornes; Josep Llados; Gemma Sanchez; Horst Bunke |

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Title |
Writer Identification in Old Handwritten Music Scores |
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2012 |
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Pattern Recognition and Signal Processing in Archaeometry: Mathematical and Computational Solutions for Archaeology |
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27-63 |
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The aim of writer identification is determining the writer of a piece of handwriting from a set of writers. In this paper we present a system for writer identification in old handwritten music scores. Even though an important amount of compositions contains handwritten text in the music scores, the aim of our work is to use only music notation to determine the author. The steps of the system proposed are the following. First of all, the music sheet is preprocessed and normalized for obtaining a single binarized music line, without the staff lines. Afterwards, 100 features are extracted for every music line, which are subsequently used in a k-NN classifier that compares every feature vector with prototypes stored in a database. By applying feature selection and extraction methods on the original feature set, the performance is increased. The proposed method has been tested on a database of old music scores from the 17th to 19th centuries, achieving a recognition rate of about 95%. |
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IGI-Global |
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Copnstantin Papaodysseus |
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Admin @ si @ FLS2012 |
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1828 |
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Author |
Miquel Ferrer; Dimosthenis Karatzas; Ernest Valveny; I. Bardaji; Horst Bunke |

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Title |
A Generic Framework for Median Graph Computation based on a Recursive Embedding Approach |
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Journal Article |
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2011 |
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Computer Vision and Image Understanding |
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CVIU |
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115 |
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7 |
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919-928 |
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Median Graph, Graph Embedding, Graph Matching, Structural Pattern Recognition |
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The median graph has been shown to be a good choice to obtain a represen- tative of a set of graphs. However, its computation is a complex problem. Recently, graph embedding into vector spaces has been proposed to obtain approximations of the median graph. The problem with such an approach is how to go from a point in the vector space back to a graph in the graph space. The main contribution of this paper is the generalization of this previ- ous method, proposing a generic recursive procedure that permits to recover the graph corresponding to a point in the vector space, introducing only the amount of approximation inherent to the use of graph matching algorithms. In order to evaluate the proposed method, we compare it with the set me- dian and with the other state-of-the-art embedding-based methods for the median graph computation. The experiments are carried out using four dif- ferent databases (one semi-artificial and three containing real-world data). Results show that with the proposed approach we can obtain better medi- ans, in terms of the sum of distances to the training graphs, than with the previous existing methods. |
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IAM @ iam @ FKV2011 |
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1831 |
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Author |
M. Visani; Oriol Ramos Terrades; Salvatore Tabbone |

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