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Author |
Chenyang Fu; Kaida Xiao; Dimosthenis Karatzas; Sophie Wuerger |
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Title |
Investigation of Unique Hue Setting Changes with Ageing |
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Journal Article |
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2011 |
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Chinese Optics Letters |
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COL |
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9 |
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5 |
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053301-1-5 |
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Clromatic sensitivity along the protan, deutan, and tritan lines and the loci of the unique hues (red, green, yellow, blue) for a very large sample (n = 185) of colour-normal observers ranging from 18 to 75 years of age are assessed. Visual judgments are obtained under normal viewing conditions using colour patches on self-luminous display under controlled adaptation conditions. Trivector discrimination thresholds show an increase as a function of age along the protan, deutan, and tritan axes, with the largest increase present along the tritan line, less pronounced shifts in unique hue settings are also observed. Based on the chromatic (protan, deutan, tritan) thresholds and using scaled cone signals, we predict the unique hue changes with ageing. A dependency on age for unique red and unique yellow for predicted hue angle is found. We conclude that the chromatic sensitivity deteriorates significantly with age, whereas the appearance of unique hues is much less affected, remaining almost constant despite the known changes in the ocular media. |
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Admin @ si @ XFW2011 |
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1818 |
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Author |
Lluis Pere de las Heras; Joan Mas; Gemma Sanchez; Ernest Valveny |
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Title |
Descriptor-based Svm Wall Detector |
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Conference Article |
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Year |
2011 |
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9th International Workshop on Graphic Recognition |
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Architectural floorplans exhibit a large variability in notation. Therefore, segmenting and identifying the elements of any kind of plan becomes a challenging task for approaches based on grouping structural primitives obtained by vectorization. Recently, a patch-based segmentation method working at pixel level and relying on the construction of a visual vocabulary has been proposed showing its adaptability to different notations by automatically learning the visual appearance of the elements in each different notation. In this paper we describe an evolution of this new approach in two directions: firstly we evaluate different features to obtain the description of every patch. Secondly, we train an SVM classifier to obtain the category of every patch instead of constructing a visual vocabulary. These modifications of the method have been tested for wall detection on two datasets of architectural floorplans with different notations and compared with the results obtained with the original approach. |
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GREC |
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Admin @ si @ HMS2011b |
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1819 |
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Author |
Partha Pratim Roy; Umapada Pal; Josep Llados |
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Title |
Document Seal Detection Using Ght and Character Proximity Graphs |
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Journal Article |
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Year |
2011 |
Publication |
Pattern Recognition |
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PR |
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44 |
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6 |
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1282-1295 |
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Seal recognition; Graphical symbol spotting; Generalized Hough transform; Multi-oriented character recognition |
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This paper deals with automatic detection of seal (stamp) from documents with cluttered background. Seal detection involves a difficult challenge due to its multi-oriented nature, arbitrary shape, overlapping of its part with signature, noise, etc. Here, a seal object is characterized by scale and rotation invariant spatial feature descriptors computed from recognition result of individual connected components (characters). Scale and rotation invariant features are used in a Support Vector Machine (SVM) classifier to recognize multi-scale and multi-oriented text characters. The concept of generalized Hough transform (GHT) is used to detect the seal and a voting scheme is designed for finding possible location of the seal in a document based on the spatial feature descriptor of neighboring component pairs. The peak of votes in GHT accumulator validates the hypothesis to locate the seal in a document. Experiment is performed in an archive of historical documents of handwritten/printed English text. Experimental results show that the method is robust in locating seal instances of arbitrary shape and orientation in documents, and also efficient in indexing a collection of documents for retrieval purposes. |
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Elsevier |
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Admin @ si @ RPL2011 |
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1820 |
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Author |
Marçal Rusiñol; V. Poulain d'Andecy; Dimosthenis Karatzas; Josep Llados |
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Title |
Classification of Administrative Document Images by Logo Identification |
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Conference Article |
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Year |
2011 |
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In proceedings of 9th IAPR Workshop on Graphic Recognition |
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This paper is focused on the categorization of administrative document images (such as invoices) based on the recognition of the supplier's graphical logo. Two different methods are proposed, the first one uses a bag-of-visual-words model whereas the second one tries to locate logo images described by the blurred shape model descriptor within documents by a sliding-window technique. Preliminar results are reported with a dataset of real administrative documents. |
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Seoul, Corea |
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GREC |
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DAG |
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Admin @ si @ RPK2011 |
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1821 |
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Author |
Alicia Fornes; Volkmar Frinken; Andreas Fischer; Jon Almazan; G. Jackson; Horst Bunke |
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Title |
A Keyword Spotting Approach Using Blurred Shape Model-Based Descriptors |
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Conference Article |
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2011 |
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Proceedings of the 2011 Workshop on Historical Document Imaging and Processing |
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83-90 |
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The automatic processing of handwritten historical documents is considered a hard problem in pattern recognition. In addition to the challenges given by modern handwritten data, a lack of training data as well as effects caused by the degradation of documents can be observed. In this scenario, keyword spotting arises to be a viable solution to make documents amenable for searching and browsing. For this task we propose the adaptation of shape descriptors used in symbol recognition. By treating each word image as a shape, it can be represented using the Blurred Shape Model and the De-formable Blurred Shape Model. Experiments on the George Washington database demonstrate that this approach is able to outperform the commonly used Dynamic Time Warping approach. |
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ACM |
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978-1-4503-0916-5 |
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HIP |
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Admin @ si @ FFF2011a |
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1823 |
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Author |
Andreas Fischer; Volkmar Frinken; Alicia Fornes; Horst Bunke |
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Title |
Transcription Alignment of Latin Manuscripts Using Hidden Markov Models |
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Conference Article |
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2011 |
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Proceedings of the 2011 Workshop on Historical Document Imaging and Processing |
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29-36 |
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Transcriptions of historical documents are a valuable source for extracting labeled handwriting images that can be used for training recognition systems. In this paper, we introduce the Saint Gall database that includes images as well as the transcription of a Latin manuscript from the 9th century written in Carolingian script. Although the available transcription is of high quality for a human reader, the spelling of the words is not accurate when compared with the handwriting image. Hence, the transcription poses several challenges for alignment regarding, e.g., line breaks, abbreviations, and capitalization. We propose an alignment system based on character Hidden Markov Models that can cope with these challenges and efficiently aligns complete document pages. On the Saint Gall database, we demonstrate that a considerable alignment accuracy can be achieved, even with weakly trained character models. |
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ACM |
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Admin @ si @ FFF2011b |
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1824 |
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Author |
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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Conference Article |
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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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LNCS |
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0302-9743 |
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978-3-642-36823-3 |
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GREC |
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DAG |
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Admin @ si @ DLP2011c |
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1825 |
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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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A Protocol to Characterize the Descriptive Power and the Complementarity of Shape Descriptors |
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Journal Article |
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2011 |
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International Journal on Document Analysis and Recognition |
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IJDAR |
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14 |
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1 |
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87-100 |
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Document analysis; Shape descriptors; Symbol description; Performance characterization; Complementarity analysis |
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Most document analysis applications rely on the extraction of shape descriptors, which may be grouped into different categories, each category having its own advantages and drawbacks (O.R. Terrades et al. in Proceedings of ICDAR’07, pp. 227–231, 2007). In order to improve the richness of their description, many authors choose to combine multiple descriptors. Yet, most of the authors who propose a new descriptor content themselves with comparing its performance to the performance of a set of single state-of-the-art descriptors in a specific applicative context (e.g. symbol recognition, symbol spotting...). This results in a proliferation of the shape descriptors proposed in the literature. In this article, we propose an innovative protocol, the originality of which is to be as independent of the final application as possible and which relies on new quantitative and qualitative measures. We introduce two types of measures: while the measures of the first type are intended to characterize the descriptive power (in terms of uniqueness, distinctiveness and robustness towards noise) of a descriptor, the second type of measures characterizes the complementarity between multiple descriptors. Characterizing upstream the complementarity of shape descriptors is an alternative to the usual approach where the descriptors to be combined are selected by trial and error, considering the performance characteristics of the overall system. To illustrate the contribution of this protocol, we performed experimental studies using a set of descriptors and a set of symbols which are widely used by the community namely ART and SC descriptors and the GREC 2003 database. |
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DAG; IF 1.091 |
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Admin @ si @VRT2011 |
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1856 |
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Marçal Rusiñol; R.Roset; Josep Llados; C.Montaner |
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Automatic Index Generation of Digitized Map Series by Coordinate Extraction and Interpretation |
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2011 |
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In Proceedings of the Sixth International Workshop on Digital Technologies in Cartographic Heritage |
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CartoHerit |
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Admin @ si @ RRL2011b |
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1978 |
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