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Author |
Albert Gordo |
![find record details (via OpenURL) openurl](http://refbase.cvc.uab.es/img/xref.gif)
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Title |
Document Image Representation, Classification and Retrieval in Large-Scale Domains |
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2013 |
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PhD Thesis, Universitat Autonoma de Barcelona-CVC |
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Despite the “paperless office” ideal that started in the decade of the seventies, businesses still strive against an increasing amount of paper documentation. Companies still receive huge amounts of paper documentation that need to be analyzed and processed, mostly in a manual way. A solution for this task consists in, first, automatically scanning the incoming documents. Then, document images can be analyzed and information can be extracted from the data. Documents can also be automatically dispatched to the appropriate workflows, used to retrieve similar documents in the dataset to transfer information, etc.
Due to the nature of this “digital mailroom”, we need document representation methods to be general, i.e., able to cope with very different types of documents. We need the methods to be sound, i.e., able to cope with unexpected types of documents, noise, etc. And, we need to methods to be scalable, i.e., able to cope with thousands or millions of documents that need to be processed, stored, and consulted. Unfortunately, current techniques of document representation, classification and retrieval are not apt for this digital mailroom framework, since they do not fulfill some or all of these requirements.
Through this thesis we focus on the problem of document representation aimed at classification and retrieval tasks under this digital mailroom framework. We first propose a novel document representation based on runlength histograms, and extend it to cope with more complex documents such as multiple-page documents, or documents that contain more sources of information such as extracted OCR text. Then we focus on the scalability requirements and propose a novel binarization method which we dubbed PCAE, as well as two general asymmetric distances between binary embeddings that can significantly improve the retrieval results at a minimal extra computational cost. Finally, we note the importance of supervised learning when performing large-scale retrieval, and study several approaches that can significantly boost the results at no extra cost at query time. |
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Address ![sorted by Address field, ascending order (up)](http://refbase.cvc.uab.es/img/sort_asc.gif) |
Barcelona |
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Ph.D. thesis |
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Ediciones Graficas Rey |
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Ernest Valveny;Florent Perronnin |
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Admin @ si @ Gor2013 |
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2277 |
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Author |
Alfons Juan-Ciscar; Gemma Sanchez |
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Title |
PRIS 2008. Pattern Recognition in Information Systems. Proceedings of the 8th international Workshop on Pattern Recognition in Information systems – PRIS 2008, in conjunction with ICEIS 2008 |
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2008 |
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Address ![sorted by Address field, ascending order (up)](http://refbase.cvc.uab.es/img/sort_asc.gif) |
Barcelona (Spain) |
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DAG @ dag @ JuS2008 |
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1054 |
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Author |
Marçal Rusiñol |
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Title |
Geometric and Structural-based Symbol Spotting. Application to Focused Retrieval in Graphic Document Collections |
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2009 |
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PhD Thesis, Universitat Autonoma de Barcelona-CVC |
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Usually, pattern recognition systems consist of two main parts. On the one hand, the data acquisition and, on the other hand, the classification of this data on a certain category. In order to recognize which category a certain query element belongs to, a set of pattern models must be provided beforehand. An off-line learning stage is needed to train the classifier and to offer a robust classification of the patterns. Within the pattern recognition field, we are interested in the recognition of graphics and, in particular, on the analysis of documents rich in graphical information. In this context, one of the main concerns is to see if the proposed systems remain scalable with respect to the data volume so as it can handle growing amounts of symbol models. In order to avoid to work with a database of reference symbols, symbol spotting and on-the-fly symbol recognition methods have been introduced in the past years.
Generally speaking, the symbol spotting problem can be defined as the identification of a set of regions of interest from a document image which are likely to contain an instance of a certain queriedn symbol without explicitly applying the whole pattern recognition scheme. Our application framework consists on indexing a collection of graphic-rich document images. This collection is
queried by example with a single instance of the symbol to look for and, by means of symbol spotting methods we retrieve the regions of interest where the symbol is likely to appear within the documents. This kind of applications are known as focused retrieval methods.
In order that the focused retrieval application can handle large collections of documents there is a need to provide an efficient access to the large volume of information that might be stored. We use indexing strategies in order to efficiently retrieve by similarity the locations where a certain part of the symbol appears. In that scenario, graphical patterns should be used as indices for accessing and navigating the collection of documents.
These indexing mechanism allow the user to search for similar elements using graphical information rather than textual queries.
Along this thesis we present a spotting architecture and different methods aiming to build a complete focused retrieval application dealing with a graphic-rich document collections. In addition, a protocol to evaluate the performance of symbol
spotting systems in terms of recognition abilities, location accuracy and scalability is proposed. |
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Address ![sorted by Address field, ascending order (up)](http://refbase.cvc.uab.es/img/sort_asc.gif) |
Barcelona (Spain) |
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Ph.D. thesis |
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Ediciones Graficas Rey |
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Josep Llados |
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DAG @ dag @ Rus2009 |
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1264 |
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Author |
Agnes Borras |
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Title |
Contributions to the Content-Based Image Retrieval Using Pictorial Queries |
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2009 |
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PhD Thesis, Universitat Autonoma de Barcelona-CVC |
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The broad access to digital cameras, personal computers and Internet, has lead to the generation of large volumes of data in digital form. If we want an effective usage of this huge amount of data, we need automatic tools to allow the retrieval of relevant information. Image data is a particular type of information that requires specific techniques of description and indexing. The computer vision field that studies these kind of techniques is called Content-Based Image Retrieval (CBIR). Instead of using text-based descriptions, a system of CBIR deals on properties that are inherent in the images themselves. Hence, the feature-based description provides a universal via of image expression in contrast with the more than 6000 languages spoken in the world.
Nowadays, the CBIR is a dynamic focus of research that has derived in important applications for many professional groups. The potential fields of application can be such diverse as: the medical domain, the crime prevention, the protection of the intel- lectual property, the journalism, the graphic design, the web search, the preservation of cultural heritage, etc.
The definition on the role of the user is a key point in the development of a CBIR application. The user is in charge to formulate the queries from which the images are retrieved. We have centered our attention on the image retrieval techniques that use queries based on pictorial information. We have identified a taxonomy composed by four main query paradigms: query-by-selection, query-by-iconic-composition, query- by-sketch and query-by-paint. Each one of these paradigms allows a different degree of user expressivity. From a simple image selection, to a complete painting of the query, the user takes control of the input in the CBIR system.
Along the chapters of this thesis we have analyzed the influence that each query paradigm imposes in the internal operations of a CBIR system. Moreover, we have proposed a set of contributions that we have exemplified in the context of a final application. |
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Address ![sorted by Address field, ascending order (up)](http://refbase.cvc.uab.es/img/sort_asc.gif) |
Barcelona (Spain) |
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Ph.D. thesis |
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Ediciones Graficas Rey |
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Bellaterra |
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Josep Llados |
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DAG; |
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DAG @ dag @ Bor2009; IAM @ iam @ Bor2009 |
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1269 |
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Author |
Antonio Clavelli; Dimosthenis Karatzas |
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Title |
Text Segmentation in Colour Posters from the Spanish Civil War Era |
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Conference Article |
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2009 |
Publication |
10th International Conference on Document Analysis and Recognition |
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181 - 185 |
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The extraction of textual content from colour documents of a graphical nature is a complicated task. The text can be rendered in any colour, size and orientation while the existence of complex background graphics with repetitive patterns can make its localization and segmentation extremely difficult.
Here, we propose a new method for extracting textual content from such colour images that makes no assumption as to the size of the characters, their orientation or colour, while it is tolerant to characters that do not follow a straight baseline. We evaluate this method on a collection of documents with historical
connotations: the Posters from the Spanish Civil War. |
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Address ![sorted by Address field, ascending order (up)](http://refbase.cvc.uab.es/img/sort_asc.gif) |
Barcelona, Spain |
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1520-5363 |
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978-1-4244-4500-4 |
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DAG @ dag @ ClK2009 |
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1172 |
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Author |
Albert Gordo; Ernest Valveny |
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Title |
A rotation invariant page layout descriptor for document classification and retrieval |
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2009 |
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10th International Conference on Document Analysis and Recognition |
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481–485 |
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Document classification usually requires of structural features such as the physical layout to obtain good accuracy rates on complex documents. This paper introduces a descriptor of the layout and a distance measure based on the cyclic dynamic time warping which can be computed in O(n2). This descriptor is translation invariant and can be easily modified to be scale and rotation invariant. Experiments with this descriptor and its rotation invariant modification are performed on the Girona archives database and compared against another common layout distance, the minimum weight edge cover. The experiments show that these methods outperform the MWEC both in accuracy and speed, particularly on rotated documents. |
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Address ![sorted by Address field, ascending order (up)](http://refbase.cvc.uab.es/img/sort_asc.gif) |
Barcelona, Spain |
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1520-5363 |
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978-1-4244-4500-4 |
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DAG @ dag @ GoV2009a |
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1175 |
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Author |
Ricard Coll; Alicia Fornes; Josep Llados |
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Title |
Graphological Analysis of Handwritten Text Documents for Human Resources Recruitment |
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Conference Article |
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2009 |
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10th International Conference on Document Analysis and Recognition |
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1081–1085 |
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The use of graphology in recruitment processes has become a popular tool in many human resources companies. This paper presents a model that links features from handwritten images to a number of personality characteristics used to measure applicant aptitudes for the job in a particular hiring scenario. In particular we propose a model of measuring active personality and leadership of the writer. Graphological features that define such a profile are measured in terms of document and script attributes like layout configuration, letter size, shape, slant and skew angle of lines, etc. After the extraction, data is classified using a neural network. An experimental framework with real samples has been constructed to illustrate the performance of the approach. |
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Address ![sorted by Address field, ascending order (up)](http://refbase.cvc.uab.es/img/sort_asc.gif) |
Barcelona, Spain |
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1520-5363 |
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978-1-4244-4500-4 |
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DAG @ dag @ CFL2009 |
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1221 |
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Partha Pratim Roy; Umapada Pal; Josep Llados |
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Title |
Seal detection and recognition: An approach for document indexing |
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Conference Article |
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2009 |
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10th International Conference on Document Analysis and Recognition |
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101–105 |
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Reliable indexing of documents having seal instances can be achieved by recognizing seal information. This paper presents a novel approach for detecting and classifying such multi-oriented seals in these documents. First, Hough Transform based methods are applied to extract the seal regions in documents. Next, isolated text characters within these regions are detected. Rotation and size invariant features and a support vector machine based classifier have been used to recognize these detected text characters. Next, for each pair of character, we encode their relative spatial organization using their distance and angular position with respect to the centre of the seal, and enter this code into a hash table. Given an input seal, we recognize the individual text characters and compute the code for pair-wise character based on the relative spatial organization. The code obtained from the input seal helps to retrieve model hypothesis from the hash table. The seal model to which we get maximum hypothesis is selected for the recognition of the input seal. The methodology is tested to index seal in rotation and size invariant environment and we obtained encouraging results. |
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Address ![sorted by Address field, ascending order (up)](http://refbase.cvc.uab.es/img/sort_asc.gif) |
Barcelona, Spain |
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1520-5363 |
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978-1-4244-4500-4 |
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DAG @ dag @ RPL2009b |
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1239 |
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Author |
Partha Pratim Roy; Umapada Pal; Josep Llados; Mathieu Nicolas Delalandre |
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Title |
Multi-Oriented and Multi-Sized Touching Character Segmentation using Dynamic Programming |
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2009 |
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10th International Conference on Document Analysis and Recognition |
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11–15 |
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In this paper, we present a scheme towards the segmentation of English multi-oriented touching strings into individual characters. When two or more characters touch, they generate a big cavity region at the background portion. Using Convex Hull information, we use these background information to find some initial points to segment a touching string into possible primitive segments (a primitive segment consists of a single character or a part of a character). Next these primitive segments are merged to get optimum segmentation and dynamic programming is applied using total likelihood of characters as the objective function. SVM classifier is used to find the likelihood of a character. To consider multi-oriented touching strings the features used in the SVM are invariant to character orientation. Circular ring and convex hull ring based approach has been used along with angular information of the contour pixels of the character to make the feature rotation invariant. From the experiment, we obtained encouraging results. |
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Address ![sorted by Address field, ascending order (up)](http://refbase.cvc.uab.es/img/sort_asc.gif) |
Barcelona, Spain |
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1520-5363 |
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978-1-4244-4500-4 |
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DAG @ dag @ RPL2009a |
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1240 |
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Author |
Robert Benavente; Gemma Sanchez; Ramon Baldrich; Maria Vanrell; Josep Llados |
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Title |
Normalized colour segmentation for human appearance description. |
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Conference Article |
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2000 |
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15 th International Conference on Pattern Recognition |
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3 |
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637-641 |
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Address ![sorted by Address field, ascending order (up)](http://refbase.cvc.uab.es/img/sort_asc.gif) |
Barcelona. |
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ICPR |
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CAT @ cat @ BSB2000 |
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223 |
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