| Records |
| Author |
Albert Gordo; Florent Perronnin |
| Title |
A Bag-of-Pages Approach to Unordered Multi-Page Document Classification |
Type |
Conference Article |
| Year |
2010 |
Publication |
20th International Conference on Pattern Recognition |
Abbreviated Journal |
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| Volume |
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Issue |
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Pages |
1920–1923 |
| Keywords |
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| Abstract |
We consider the problem of classifying documents containing multiple unordered pages. For this purpose, we propose a novel bag-of-pages document representation. To represent a document, one assigns every page to a prototype in a codebook of pages. This leads to a histogram representation which can then be fed to any discriminative classifier. We also consider several refinements over this initial approach. We show on two challenging datasets that the proposed approach significantly outperforms a baseline system. |
| Address |
Istanbul (Turkey) |
| Corporate Author |
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Thesis |
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| Publisher |
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Place of Publication |
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Editor |
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| Language |
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Summary Language |
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Original Title |
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| Series Editor |
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Series Title |
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Abbreviated Series Title |
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| Series Volume |
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Series Issue |
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Edition |
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| ISSN |
1051-4651 |
ISBN |
978-1-4244-7542-1 |
Medium |
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| Area |
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Expedition |
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Conference |
ICPR |
Notes  |
DAG |
Approved |
no |
| Call Number |
Admin @ si @ GoP2010 |
Serial |
1480 |
| Permanent link to this record |
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| Author |
Palaiahnakote Shivakumara; Anjan Dutta; Trung Quy Phan; Chew Lim Tan; Umapada Pal |
| Title |
A Novel Mutual Nearest Neighbor based Symmetry for Text Frame Classification in Video |
Type |
Journal Article |
| Year |
2011 |
Publication |
Pattern Recognition |
Abbreviated Journal |
PR |
| Volume |
44 |
Issue |
8 |
Pages |
1671-1683 |
| Keywords |
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| Abstract |
In the field of multimedia retrieval in video, text frame classification is essential for text detection, event detection, event boundary detection, etc. We propose a new text frame classification method that introduces a combination of wavelet and median moment with k-means clustering to select probable text blocks among 16 equally sized blocks of a video frame. The same feature combination is used with a new Max–Min clustering at the pixel level to choose probable dominant text pixels in the selected probable text blocks. For the probable text pixels, a so-called mutual nearest neighbor based symmetry is explored with a four-quadrant formation centered at the centroid of the probable dominant text pixels to know whether a block is a true text block or not. If a frame produces at least one true text block then it is considered as a text frame otherwise it is a non-text frame. Experimental results on different text and non-text datasets including two public datasets and our own created data show that the proposed method gives promising results in terms of recall and precision at the block and frame levels. Further, we also show how existing text detection methods tend to misclassify non-text frames as text frames in term of recall and precision at both the block and frame levels. |
| Address |
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| Corporate Author |
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Place of Publication |
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Editor |
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| Language |
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Summary Language |
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Original Title |
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| Series Editor |
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Series Title |
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Abbreviated Series Title |
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| Series Volume |
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Series Issue |
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Edition |
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| ISSN |
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ISBN |
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Medium |
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| Area |
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Expedition |
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Conference |
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| Notes |
DAG |
Approved |
no |
| Call Number |
Admin @ si @ SDP2011 |
Serial |
1727 |
| Permanent link to this record |
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| |
| Author |
Lluis Pere de las Heras; Gemma Sanchez |
| Title |
And-Or Graph Grammar for Architectural Floorplan Representation, Learning and Recognition. A Semantic, Structural and Hierarchical Model |
Type |
Conference Article |
| Year |
2011 |
Publication |
5th Iberian Conference on Pattern Recognition and Image Analysis |
Abbreviated Journal |
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| Volume |
6669 |
Issue |
|
Pages |
17-24 |
| Keywords |
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| Abstract |
This paper presents a syntactic model for architectural floor plan interpretation. A stochastic image grammar over an And-Or graph is inferred to represent the hierarchical, structural and semantic relations between elements of all possible floor plans. This grammar is augmented with three different probabilistic models, learnt from a training set, to account the frequency of that relations. Then, a Bottom-Up/Top-Down parser with a pruning strategy has been used for floor plan recognition. For a given input, the parser generates the most probable parse graph for that document. This graph not only contains the structural and semantic relations of its elements, but also its hierarchical composition, that allows to interpret the floor plan at different levels of abstraction. |
| Address |
Las Palmas de Gran Canaria. Spain |
| Corporate Author |
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Thesis |
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| Publisher |
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Place of Publication |
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Editor |
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| Language |
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Summary Language |
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Original Title |
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| Series Editor |
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Series Title |
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Abbreviated Series Title |
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| Series Volume |
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Series Issue |
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Edition |
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| ISSN |
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ISBN |
978-3-642-21256-7 |
Medium |
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| Area |
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Expedition |
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Conference |
IbPRIA |
| Notes |
DAG |
Approved |
no |
| Call Number |
Admin @ si @ HeS2011 |
Serial |
1736 |
| Permanent link to this record |
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| |
| Author |
Anjan Dutta; Josep Llados; Umapada Pal |
| Title |
A Bag-of-Paths Based Serialized Subgraph Matching for Symbol Spotting in Line Drawings |
Type |
Conference Article |
| Year |
2011 |
Publication |
5th Iberian Conference on Pattern Recognition and Image Analysis |
Abbreviated Journal |
|
| Volume |
6669 |
Issue |
|
Pages |
620-627 |
| Keywords |
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| Abstract |
In this paper we propose an error tolerant subgraph matching algorithm based on bag-of-paths for solving the problem of symbol spotting in line drawings. Bag-of-paths is a factorized representation of graphs where the factorization is done by considering all the acyclic paths between each pair of connected nodes. Similar paths within the whole collection of documents are clustered and organized in a lookup table for efficient indexing. The lookup table contains the index key of each cluster and the corresponding list of locations as a single entry. The mean path of each of the clusters serves as the index key for each table entry. The spotting method is then formulated by a spatial voting scheme to the list of locations of the paths that are decided in terms of search of similar paths that compose the query symbol. Efficient indexing of common substructures helps to reduce the computational burden of usual graph based methods. The proposed method can also be seen as a way to serialize graphs which allows to reduce the complexity of the subgraph isomorphism. We have encoded the paths in terms of both attributed strings and turning functions, and presented a comparative results between them within the symbol spotting framework. Experimentations for matching different shape silhouettes are also reported and the method has been proved to work in noisy environment also. |
| Address |
Las Palmas de Gran Canaria. Spain |
| Corporate Author |
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Thesis |
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| Publisher |
Springer Berlin Heidelberg |
Place of Publication |
Berlin |
Editor |
Jordi Vitria; Joao Miguel Raposo; Mario Hernandez |
| Language |
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Summary Language |
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Original Title |
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| Series Editor |
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Series Title |
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Abbreviated Series Title |
LNCS |
| Series Volume |
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Series Issue |
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Edition |
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| ISSN |
0302-9743 |
ISBN |
978-3-642-21256-7 |
Medium |
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| Area |
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Expedition |
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Conference |
IbPRIA |
| Notes |
DAG |
Approved |
no |
| Call Number |
Admin @ si @ DLP2011a |
Serial |
1738 |
| Permanent link to this record |
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| |
| Author |
David Fernandez; Josep Llados; Alicia Fornes |
| Title |
Handwritten Word Spotting in Old Manuscript Images Using a Pseudo-Structural Descriptor Organized in a Hash Structure |
Type |
Conference Article |
| Year |
2011 |
Publication |
5th Iberian Conference on Pattern Recognition and Image Analysis |
Abbreviated Journal |
|
| Volume |
6669 |
Issue |
|
Pages |
628-635 |
| Keywords |
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| Abstract |
There are lots of historical handwritten documents with information that can be used for several studies and projects. The Document Image Analysis and Recognition community is interested in preserving these documents and extracting all the valuable information from them. Handwritten word-spotting is the pattern classification task which consists in detecting handwriting word images. In this work, we have used a query-by-example formalism: we have matched an input image with one or multiple images from handwritten documents to determine the distance that might indicate a correspondence. We have developed an approach based in characteristic Loci Features stored in a hash structure. Document images of the marriage licences of the Cathedral of Barcelona are used as the benchmarking database. |
| Address |
Las Palmas de Gran Canaria. Spain |
| Corporate Author |
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Thesis |
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| Publisher |
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Place of Publication |
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Editor |
Jordi Vitria; Joao Miguel Raposo; Mario Hernandez |
| Language |
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Summary Language |
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Original Title |
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| Series Editor |
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Series Title |
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Abbreviated Series Title |
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| Series Volume |
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Series Issue |
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Edition |
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| ISSN |
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ISBN |
978-3-642-21256-7 |
Medium |
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| Area |
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Expedition |
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Conference |
IbPRIA |
| Notes |
DAG |
Approved |
no |
| Call Number |
Admin @ si @ FLF2011 |
Serial |
1742 |
| Permanent link to this record |
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| Author |
Jaume Gibert; Ernest Valveny; Horst Bunke |
| Title |
Dimensionality Reduction for Graph of Words Embedding |
Type |
Conference Article |
| Year |
2011 |
Publication |
8th IAPR-TC-15 International Workshop. Graph-Based Representations in Pattern Recognition |
Abbreviated Journal |
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| Volume |
6658 |
Issue |
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Pages |
22-31 |
| Keywords |
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| Abstract |
The Graph of Words Embedding consists in mapping every graph of a given dataset to a feature vector by counting unary and binary relations between node attributes of the graph. While it shows good properties in classification problems, it suffers from high dimensionality and sparsity. These two issues are addressed in this article. Two well-known techniques for dimensionality reduction, kernel principal component analysis (kPCA) and independent component analysis (ICA), are applied to the embedded graphs. We discuss their performance compared to the classification of the original vectors on three different public databases of graphs. |
| Address |
Münster, Germany |
| Corporate Author |
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Thesis |
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| Publisher |
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Place of Publication |
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Editor |
Xiaoyi Jiang; Miquel Ferrer; Andrea Torsello |
| Language |
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Summary Language |
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Original Title |
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| Series Editor |
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Series Title |
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Abbreviated Series Title |
LNCS |
| Series Volume |
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Series Issue |
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Edition |
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| ISSN |
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ISBN |
978-3-642-20843-0 |
Medium |
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| Area |
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Expedition |
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Conference |
GbRPR |
| Notes |
DAG |
Approved |
no |
| Call Number |
Admin @ si @ GVB2011a |
Serial |
1743 |
| Permanent link to this record |
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| Author |
Jaume Gibert; Ernest Valveny; Horst Bunke |
| Title |
Vocabulary Selection for Graph of Words Embedding |
Type |
Conference Article |
| Year |
2011 |
Publication |
5th Iberian Conference on Pattern Recognition and Image Analysis |
Abbreviated Journal |
|
| Volume |
6669 |
Issue |
|
Pages |
216-223 |
| Keywords |
|
| Abstract |
The Graph of Words Embedding consists in mapping every graph in a given dataset to a feature vector by counting unary and binary relations between node attributes of the graph. It has been shown to perform well for graphs with discrete label alphabets. In this paper we extend the methodology to graphs with n-dimensional continuous attributes by selecting node representatives. We propose three different discretization procedures for the attribute space and experimentally evaluate the dependence on both the selector and the number of node representatives. In the context of graph classification, the experimental results reveal that on two out of three public databases the proposed extension achieves superior performance over a standard reference system. |
| Address |
Las Palmas de Gran Canaria. Spain |
| Corporate Author |
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Thesis |
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| Publisher |
Springer |
Place of Publication |
Berlin |
Editor |
Vitria, Jordi; Sanches, João Miguel Raposo; Hernández, Mario |
| Language |
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Summary Language |
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Original Title |
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| Series Editor |
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Series Title |
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Abbreviated Series Title |
LNCS |
| Series Volume |
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Series Issue |
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Edition |
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| ISSN |
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ISBN |
978-3-642-21256-7 |
Medium |
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| Area |
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Expedition |
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Conference |
IbPRIA |
| Notes |
DAG |
Approved |
no |
| Call Number |
Admin @ si @ GVB2011b |
Serial |
1744 |
| Permanent link to this record |
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| Author |
Jaume Gibert; Ernest Valveny; Oriol Ramos Terrades; Horst Bunke |
| Title |
Multiple Classifiers for Graph of Words Embedding |
Type |
Conference Article |
| Year |
2011 |
Publication |
10th International Conference on Multiple Classifier Systems |
Abbreviated Journal |
|
| Volume |
6713 |
Issue |
|
Pages |
36-45 |
| Keywords |
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| Abstract |
During the last years, there has been an increasing interest in applying the multiple classifier framework to the domain of structural pattern recognition. Constructing base classifiers when the input patterns are graph based representations is not an easy problem. In this work, we make use of the graph embedding methodology in order to construct different feature vector representations for graphs. The graph of words embedding assigns a feature vector to every graph by counting unary and binary relations between node representatives and combining these pieces of information into a single vector. Selecting different node representatives leads to different vectorial representations and therefore to different base classifiers that can be combined. We experimentally show how this methodology significantly improves the classification of graphs with respect to single base classifiers. |
| Address |
Napoles, Italy |
| Corporate Author |
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Thesis |
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| Publisher |
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Place of Publication |
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Editor |
Carlo Sansone; Josef Kittler; Fabio Roli |
| Language |
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Summary Language |
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Original Title |
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| Series Editor |
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Series Title |
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Abbreviated Series Title |
LNCS |
| Series Volume |
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Series Issue |
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Edition |
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| ISSN |
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ISBN |
978-3-642-21556-8 |
Medium |
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| Area |
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Expedition |
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Conference |
MCS |
| Notes |
DAG |
Approved |
no |
| Call Number |
Admin @ si @GVR2011 |
Serial |
1745 |
| Permanent link to this record |
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| Author |
Jon Almazan; Alicia Fornes; Ernest Valveny |
| Title |
A Non-Rigid Feature Extraction Method for Shape Recognition |
Type |
Conference Article |
| Year |
2011 |
Publication |
11th International Conference on Document Analysis and Recognition |
Abbreviated Journal |
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| Volume |
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Issue |
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Pages |
987-991 |
| Keywords |
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| Abstract |
This paper presents a methodology for shape recognition that focuses on dealing with the difficult problem of large deformations. The proposed methodology consists in a novel feature extraction technique, which uses a non-rigid representation adaptable to the shape. This technique employs a deformable grid based on the computation of geometrical centroids that follows a region partitioning algorithm. Then, a feature vector is extracted by computing pixel density measures around these geometrical centroids. The result is a shape descriptor that adapts its representation to the given shape and encodes the pixel density distribution. The validity of the method when dealing with large deformations has been experimentally shown over datasets composed of handwritten shapes. It has been applied to signature verification and shape recognition tasks demonstrating high accuracy and low computational cost. |
| Address |
Beijing; China; September 2011 |
| Corporate Author |
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Thesis |
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| Publisher |
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Place of Publication |
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Editor |
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| Language |
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Summary Language |
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Original Title |
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| Series Editor |
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Series Title |
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Abbreviated Series Title |
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| Series Volume |
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Series Issue |
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Edition |
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| ISSN |
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ISBN |
978-0-7695-4520-2 |
Medium |
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Expedition |
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Conference |
ICDAR |
| Notes |
DAG |
Approved |
no |
| Call Number |
Admin @ si @ AFV2011 |
Serial |
1763 |
| Permanent link to this record |
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| Author |
Marçal Rusiñol; R.Roset; Josep Llados; C.Montaner |
| Title |
Automatic Index Generation of Digitized Map Series by Coordinate Extraction and Interpretation |
Type |
Journal |
| Year |
2011 |
Publication |
e-Perimetron |
Abbreviated Journal |
ePER |
| Volume |
6 |
Issue |
4 |
Pages |
219-229 |
| Keywords |
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| Abstract |
By means of computer vision algorithms scanned images of maps are processed in order to extract relevant geographic information from printed coordinate pairs. The meaningful information is then transformed into georeferencing information for each single map sheet, and the complete set is compiled to produce a graphical index sheet for the map series along with relevant metadata. The whole process is fully automated and trained to attain maximum effectivity and throughput. |
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Thesis |
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Place of Publication |
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Editor |
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Summary Language |
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Original Title |
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| Series Editor |
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Series Title |
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Abbreviated Series Title |
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Series Issue |
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Edition |
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ISBN |
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Medium |
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Expedition |
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Conference |
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| Notes |
DAG |
Approved |
no |
| Call Number |
Admin @ si @ RRL2011a |
Serial |
1765 |
| Permanent link to this record |
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| Author |
Volkmar Frinken; Andreas Fischer; Horst Bunke; Alicia Fornes |
| Title |
Co-training for Handwritten Word Recognition |
Type |
Conference Article |
| Year |
2011 |
Publication |
11th International Conference on Document Analysis and Recognition |
Abbreviated Journal |
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| Volume |
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Issue |
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Pages |
314-318 |
| Keywords |
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| Abstract |
To cope with the tremendous variations of writing styles encountered between different individuals, unconstrained automatic handwriting recognition systems need to be trained on large sets of labeled data. Traditionally, the training data has to be labeled manually, which is a laborious and costly process. Semi-supervised learning techniques offer methods to utilize unlabeled data, which can be obtained cheaply in large amounts in order, to reduce the need for labeled data. In this paper, we propose the use of Co-Training for improving the recognition accuracy of two weakly trained handwriting recognition systems. The first one is based on Recurrent Neural Networks while the second one is based on Hidden Markov Models. On the IAM off-line handwriting database we demonstrate a significant increase of the recognition accuracy can be achieved with Co-Training for single word recognition. |
| Address |
Beijing, China |
| Corporate Author |
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Thesis |
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| Publisher |
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Place of Publication |
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Editor |
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| Language |
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Summary Language |
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Original Title |
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| Series Editor |
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Series Title |
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Abbreviated Series Title |
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| Series Volume |
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Series Issue |
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Edition |
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| ISSN |
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ISBN |
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Medium |
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| Area |
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Expedition |
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Conference |
ICDAR |
| Notes |
DAG |
Approved |
no |
| Call Number |
Admin @ si @ FFB2011 |
Serial |
1789 |
| Permanent link to this record |
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| Author |
Muhammad Muzzamil Luqman; Jean-Yves Ramel; Josep Llados; Thierry Brouard |
| Title |
Subgraph Spotting Through Explicit Graph Embedding: An Application to Content Spotting in Graphic Document Images |
Type |
Conference Article |
| Year |
2011 |
Publication |
11th International Conference on Document Analysis and Recognition |
Abbreviated Journal |
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| Volume |
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Issue |
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Pages |
870-874 |
| Keywords |
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| Abstract |
We present a method for spotting a subgraph in a graph repository. Subgraph spotting is a very interesting research problem for various application domains where the use of a relational data structure is mandatory. Our proposed method accomplishes subgraph spotting through graph embedding. We achieve automatic indexation of a graph repository during off-line learning phase, where we (i) break the graphs into 2-node sub graphs (a.k.a. cliques of order 2), which are primitive building-blocks of a graph, (ii) embed the 2-node sub graphs into feature vectors by employing our recently proposed explicit graph embedding technique, (iii) cluster the feature vectors in classes by employing a classic agglomerative clustering technique, (iv) build an index for the graph repository and (v) learn a Bayesian network classifier. The subgraph spotting is achieved during the on-line querying phase, where we (i) break the query graph into 2-node sub graphs, (ii) embed them into feature vectors, (iii) employ the Bayesian network classifier for classifying the query 2-node sub graphs and (iv) retrieve the respective graphs by looking-up in the index of the graph repository. The graphs containing all query 2-node sub graphs form the set of result graphs for the query. Finally, we employ the adjacency matrix of each result graph along with a score function, for spotting the query graph in it. The proposed subgraph spotting method is equally applicable to a wide range of domains, offering ease of query by example (QBE) and granularity of focused retrieval. Experimental results are presented for graphs generated from two repositories of electronic and architectural document images. |
| Address |
Beijing, China |
| Corporate Author |
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Thesis |
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| Publisher |
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Place of Publication |
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Editor |
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| Language |
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Summary Language |
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Original Title |
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| Series Editor |
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Series Title |
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Abbreviated Series Title |
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| Series Volume |
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Series Issue |
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Edition |
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| ISSN |
1520-5363 |
ISBN |
978-1-4577-1350-7 |
Medium |
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| Area |
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Expedition |
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Conference |
ICDAR |
| Notes |
DAG |
Approved |
no |
| Call Number |
Admin @ si @ LRL2011 |
Serial |
1790 |
| Permanent link to this record |
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| Author |
Anjan Dutta; Josep Llados; Umapada Pal |
| Title |
Symbol Spotting in Line Drawings Through Graph Paths Hashing |
Type |
Conference Article |
| Year |
2011 |
Publication |
11th International Conference on Document Analysis and Recognition |
Abbreviated Journal |
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| Volume |
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Issue |
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Pages |
982-986 |
| Keywords |
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| Abstract |
In this paper we propose a symbol spotting technique through hashing the shape descriptors of graph paths (Hamiltonian paths). Complex graphical structures in line drawings can be efficiently represented by graphs, which ease the accurate localization of the model symbol. Graph paths are the factorized substructures of graphs which enable robust recognition even in the presence of noise and distortion. In our framework, the entire database of the graphical documents is indexed in hash tables by the locality sensitive hashing (LSH) of shape descriptors of the paths. The hashing data structure aims to execute an approximate k-NN search in a sub-linear time. The spotting method is formulated by a spatial voting scheme to the list of locations of the paths that are decided during the hash table lookup process. We perform detailed experiments with various dataset of line drawings and the results demonstrate the effectiveness and efficiency of the technique. |
| Address |
Beijing, China |
| Corporate Author |
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Thesis |
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| Publisher |
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Place of Publication |
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Editor |
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| Language |
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Summary Language |
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Original Title |
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| Series Editor |
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Series Title |
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Abbreviated Series Title |
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| Series Volume |
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Series Issue |
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Edition |
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| ISSN |
1520-5363 |
ISBN |
978-1-4577-1350-7 |
Medium |
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| Area |
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Expedition |
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Conference |
ICDAR |
| Notes |
DAG |
Approved |
no |
| Call Number |
Admin @ si @ DLP2011b |
Serial |
1791 |
| Permanent link to this record |
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| Author |
Lluis Pere de las Heras; Joan Mas; Gemma Sanchez; Ernest Valveny |
| Title |
Wall Patch-Based Segmentation in Architectural Floorplans |
Type |
Conference Article |
| Year |
2011 |
Publication |
11th International Conference on Document Analysis and Recognition |
Abbreviated Journal |
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| Volume |
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Issue |
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Pages |
1270-1274 |
| Keywords |
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| Abstract |
Segmentation of architectural floor plans is a challenging task, mainly because of the large variability in the notation between different plans. In general, traditional techniques, usually based on analyzing and grouping structural primitives obtained by vectorization, are only able to handle a reduced range of similar notations. In this paper we propose an alternative patch-based segmentation approach working at pixel level, without need of vectorization. The image is divided into a set of patches and a set of features is extracted for every patch. Then, each patch is assigned to a visual word of a previously learned vocabulary and given a probability of belonging to each class of objects. Finally, a post-process assigns the final label for every pixel. This approach has been applied to the detection of walls on two datasets of architectural floor plans with different notations, achieving high accuracy rates. |
| Address |
Beiging, China |
| Corporate Author |
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Thesis |
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| Publisher |
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Place of Publication |
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Editor |
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| Language |
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Summary Language |
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Original Title |
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| Series Editor |
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Series Title |
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Abbreviated Series Title |
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| Series Volume |
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Series Issue |
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Edition |
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| ISSN |
1520-5363 |
ISBN |
978-0-7695-4520-2 |
Medium |
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Expedition |
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Conference |
ICDAR |
| Notes |
DAG |
Approved |
no |
| Call Number |
Admin @ si @ HMS2011a |
Serial |
1792 |
| Permanent link to this record |
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| Author |
Dimosthenis Karatzas; Sergi Robles; Joan Mas; Farshad Nourbakhsh; Partha Pratim Roy |
| Title |
ICDAR 2011 Robust Reading Competition – Challege 1: Reading Text in Born-Digital Images (Web and Email) |
Type |
Conference Article |
| Year |
2011 |
Publication |
11th International Conference on Document Analysis and Recognition |
Abbreviated Journal |
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| Volume |
|
Issue |
|
Pages |
1485-1490 |
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This paper presents the results of the first Challenge of ICDAR 2011 Robust Reading Competition. Challenge 1 is focused on the extraction of text from born-digital images, specifically from images found in Web pages and emails. The challenge was organized in terms of three tasks that look at different stages of the process: text localization, text segmentation and word recognition. In this paper we present the results of the challenge for all three tasks, and make an open call for continuous participation outside the context of ICDAR 2011. |
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Beijing, China |
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1520-5363 |
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978-1-4577-1350-7 |
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ICDAR |
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Admin @ si @ KRM2011 |
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1793 |
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