|
Records |
Links |
|
Author |
Pau Riba; Josep Llados; Alicia Fornes; Anjan Dutta |

|
|
Title |
Large-scale graph indexing using binary embeddings of node contexts for information spotting in document image databases |
Type |
Journal Article |
|
Year |
2017 |
Publication |
Pattern Recognition Letters |
Abbreviated Journal |
PRL |
|
|
Volume |
87 |
Issue  |
|
Pages |
203-211 |
|
|
Keywords |
|
|
|
Abstract |
Graph-based representations are experiencing a growing usage in visual recognition and retrieval due to their representational power in front of classical appearance-based representations. However, retrieving a query graph from a large dataset of graphs implies a high computational complexity. The most important property for a large-scale retrieval is the search time complexity to be sub-linear in the number of database examples. With this aim, in this paper we propose a graph indexation formalism applied to visual retrieval. A binary embedding is defined as hashing keys for graph nodes. Given a database of labeled graphs, graph nodes are complemented with vectors of attributes representing their local context. Then, each attribute vector is converted to a binary code applying a binary-valued hash function. Therefore, graph retrieval is formulated in terms of finding target graphs in the database whose nodes have a small Hamming distance from the query nodes, easily computed with bitwise logical operators. As an application example, we validate the performance of the proposed methods in different real scenarios such as handwritten word spotting in images of historical documents or symbol spotting in architectural floor plans. |
|
|
Address |
|
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
|
Place of Publication |
|
Editor |
|
|
|
Language |
|
Summary Language |
|
Original Title |
|
|
|
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
|
Series Volume |
|
Series Issue |
|
Edition |
|
|
|
ISSN |
|
ISBN |
|
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
|
|
|
Notes |
DAG; 600.097; 602.006; 603.053; 600.121 |
Approved |
no |
|
|
Call Number |
RLF2017b |
Serial |
2873 |
|
Permanent link to this record |
|
|
|
|
Author |
Lluis Gomez; Dimosthenis Karatzas |


|
|
Title |
TextProposals: a Text‐specific Selective Search Algorithm for Word Spotting in the Wild |
Type |
Journal Article |
|
Year |
2017 |
Publication |
Pattern Recognition |
Abbreviated Journal |
PR |
|
|
Volume |
70 |
Issue  |
|
Pages |
60-74 |
|
|
Keywords |
|
|
|
Abstract |
Motivated by the success of powerful while expensive techniques to recognize words in a holistic way (Goel et al., 2013; Almazán et al., 2014; Jaderberg et al., 2016) object proposals techniques emerge as an alternative to the traditional text detectors. In this paper we introduce a novel object proposals method that is specifically designed for text. We rely on a similarity based region grouping algorithm that generates a hierarchy of word hypotheses. Over the nodes of this hierarchy it is possible to apply a holistic word recognition method in an efficient way.
Our experiments demonstrate that the presented method is superior in its ability of producing good quality word proposals when compared with class-independent algorithms. We show impressive recall rates with a few thousand proposals in different standard benchmarks, including focused or incidental text datasets, and multi-language scenarios. Moreover, the combination of our object proposals with existing whole-word recognizers (Almazán et al., 2014; Jaderberg et al., 2016) shows competitive performance in end-to-end word spotting, and, in some benchmarks, outperforms previously published results. Concretely, in the challenging ICDAR2015 Incidental Text dataset, we overcome in more than 10% F-score the best-performing method in the last ICDAR Robust Reading Competition (Karatzas, 2015). Source code of the complete end-to-end system is available at https://github.com/lluisgomez/TextProposals. |
|
|
Address |
|
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
|
Place of Publication |
|
Editor |
|
|
|
Language |
|
Summary Language |
|
Original Title |
|
|
|
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
|
Series Volume |
|
Series Issue |
|
Edition |
|
|
|
ISSN |
|
ISBN |
|
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
|
|
|
Notes |
DAG; 600.084; 601.197; 600.121; 600.129 |
Approved |
no |
|
|
Call Number |
Admin @ si @ GoK2017 |
Serial |
2886 |
|
Permanent link to this record |
|
|
|
|
Author |
Lluis Gomez; Anguelos Nicolaou; Dimosthenis Karatzas |


|
|
Title |
Improving patch‐based scene text script identification with ensembles of conjoined networks |
Type |
Journal Article |
|
Year |
2017 |
Publication |
Pattern Recognition |
Abbreviated Journal |
PR |
|
|
Volume |
67 |
Issue  |
|
Pages |
85-96 |
|
|
Keywords |
|
|
|
Abstract |
|
|
|
Address |
|
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
|
Place of Publication |
|
Editor |
|
|
|
Language |
|
Summary Language |
|
Original Title |
|
|
|
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
|
Series Volume |
|
Series Issue |
|
Edition |
|
|
|
ISSN |
|
ISBN |
|
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
|
|
|
Notes |
DAG; 600.084; 600.121; 600.129 |
Approved |
no |
|
|
Call Number |
Admin @ si @ GNK2017 |
Serial |
2887 |
|
Permanent link to this record |
|
|
|
|
Author |
Alicia Fornes; Josep Llados; Oriol Ramos Terrades; Marçal Rusiñol |

|
|
Title |
La Visió per Computador com a Eina per a la Interpretació Automàtica de Fonts Documentals |
Type |
Journal |
|
Year |
2016 |
Publication |
Lligall, Revista Catalana d'Arxivística |
Abbreviated Journal |
|
|
|
Volume |
39 |
Issue  |
|
Pages |
20-46 |
|
|
Keywords |
|
|
|
Abstract |
|
|
|
Address |
|
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
|
Place of Publication |
|
Editor |
|
|
|
Language |
|
Summary Language |
|
Original Title |
|
|
|
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
|
Series Volume |
|
Series Issue |
|
Edition |
|
|
|
ISSN |
|
ISBN |
|
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
|
|
|
Notes |
DAG; 600.097 |
Approved |
no |
|
|
Call Number |
Admin @ si @ FLR2016 |
Serial |
2897 |
|
Permanent link to this record |
|
|
|
|
Author |
Anjan Dutta; Josep Llados; Horst Bunke; Umapada Pal |


|
|
Title |
Product graph-based higher order contextual similarities for inexact subgraph matching |
Type |
Journal Article |
|
Year |
2018 |
Publication |
Pattern Recognition |
Abbreviated Journal |
PR |
|
|
Volume |
76 |
Issue  |
|
Pages |
596-611 |
|
|
Keywords |
|
|
|
Abstract |
Many algorithms formulate graph matching as an optimization of an objective function of pairwise quantification of nodes and edges of two graphs to be matched. Pairwise measurements usually consider local attributes but disregard contextual information involved in graph structures. We address this issue by proposing contextual similarities between pairs of nodes. This is done by considering the tensor product graph (TPG) of two graphs to be matched, where each node is an ordered pair of nodes of the operand graphs. Contextual similarities between a pair of nodes are computed by accumulating weighted walks (normalized pairwise similarities) terminating at the corresponding paired node in TPG. Once the contextual similarities are obtained, we formulate subgraph matching as a node and edge selection problem in TPG. We use contextual similarities to construct an objective function and optimize it with a linear programming approach. Since random walk formulation through TPG takes into account higher order information, it is not a surprise that we obtain more reliable similarities and better discrimination among the nodes and edges. Experimental results shown on synthetic as well as real benchmarks illustrate that higher order contextual similarities increase discriminating power and allow one to find approximate solutions to the subgraph matching problem. |
|
|
Address |
|
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
|
Place of Publication |
|
Editor |
|
|
|
Language |
|
Summary Language |
|
Original Title |
|
|
|
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
|
Series Volume |
|
Series Issue |
|
Edition |
|
|
|
ISSN |
|
ISBN |
|
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
|
|
|
Notes |
DAG; 602.167; 600.097; 600.121 |
Approved |
no |
|
|
Call Number |
Admin @ si @ DLB2018 |
Serial |
3083 |
|
Permanent link to this record |