|
Records |
Links |
|
Author |
Marçal Rusiñol; Josep Llados; Philippe Dosch |

|
|
Title |
Camera-Based Graphical Symbol Detection |
Type |
Conference Article |
|
Year |
2007 |
Publication |
9th IEEE International Conference on Document Analysis and Recognition |
Abbreviated Journal |
|
|
|
Volume |
2 |
Issue |
|
Pages  |
884–888 |
|
|
Keywords |
|
|
|
Abstract |
|
|
|
Address |
Curitiba (Brazil) |
|
|
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 |
ICDAR |
|
|
Notes |
DAG |
Approved |
no |
|
|
Call Number |
DAG @ dag @ RLD2007 |
Serial |
848 |
|
Permanent link to this record |
|
|
|
|
Author |
Sergi Garcia Bordils; Dimosthenis Karatzas; Marçal Rusiñol |


|
|
Title |
STEP – Towards Structured Scene-Text Spotting |
Type |
Conference Article |
|
Year |
2024 |
Publication |
Winter Conference on Applications of Computer Vision |
Abbreviated Journal |
|
|
|
Volume |
|
Issue |
|
Pages  |
883-892 |
|
|
Keywords |
|
|
|
Abstract |
We introduce the structured scene-text spotting task, which requires a scene-text OCR system to spot text in the wild according to a query regular expression. Contrary to generic scene text OCR, structured scene-text spotting seeks to dynamically condition both scene text detection and recognition on user-provided regular expressions. To tackle this task, we propose the Structured TExt sPotter (STEP), a model that exploits the provided text structure to guide the OCR process. STEP is able to deal with regular expressions that contain spaces and it is not bound to detection at the word-level granularity. Our approach enables accurate zero-shot structured text spotting in a wide variety of real-world reading scenarios and is solely trained on publicly available data. To demonstrate the effectiveness of our approach, we introduce a new challenging test dataset that contains several types of out-of-vocabulary structured text, reflecting important reading applications of fields such as prices, dates, serial numbers, license plates etc. We demonstrate that STEP can provide specialised OCR performance on demand in all tested scenarios. |
|
|
Address |
Waikoloa; Hawai; USA; January 2024 |
|
|
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 |
WACV |
|
|
Notes |
DAG |
Approved |
no |
|
|
Call Number |
Admin @ si @ GKR2024 |
Serial |
3992 |
|
Permanent link to this record |
|
|
|
|
Author |
Suman Ghosh; Ernest Valveny |


|
|
Title |
Query by String word spotting based on character bi-gram indexing |
Type |
Conference Article |
|
Year |
2015 |
Publication |
13th International Conference on Document Analysis and Recognition ICDAR2015 |
Abbreviated Journal |
|
|
|
Volume |
|
Issue |
|
Pages  |
881-885 |
|
|
Keywords |
|
|
|
Abstract |
In this paper we propose a segmentation-free query by string word spotting method. Both the documents and query strings are encoded using a recently proposed word representa- tion that projects images and strings into a common atribute space based on a pyramidal histogram of characters(PHOC). These attribute models are learned using linear SVMs over the Fisher Vector representation of the images along with the PHOC labels of the corresponding strings. In order to search through the whole page, document regions are indexed per character bi- gram using a similar attribute representation. On top of that, we propose an integral image representation of the document using a simplified version of the attribute model for efficient computation. Finally we introduce a re-ranking step in order to boost retrieval performance. We show state-of-the-art results for segmentation-free query by string word spotting in single-writer and multi-writer standard datasets |
|
|
Address |
Nancy; France; August 2015 |
|
|
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 |
ICDAR |
|
|
Notes |
DAG; 600.077 |
Approved |
no |
|
|
Call Number |
Admin @ si @ GhV2015a |
Serial |
2715 |
|
Permanent link to this record |
|
|
|
|
Author |
Maria Vanrell; Felipe Lumbreras; A. Pujol; Ramon Baldrich; Josep Llados; Juan J. Villanueva |

|
|
Title |
Colour Normalisation Based on Background Information. |
Type |
Miscellaneous |
|
Year |
2001 |
Publication |
Proceeding ICIP 2001, IEEE International Conference on Image Processing |
Abbreviated Journal |
ICIP 2001 |
|
|
Volume |
|
Issue |
1 |
Pages  |
874–877 |
|
|
Keywords |
|
|
|
Abstract |
|
|
|
Address |
Grecia. |
|
|
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 |
ADAS;DAG;CIC |
Approved |
no |
|
|
Call Number |
ADAS @ adas @ VLP2001 |
Serial |
167 |
|
Permanent link to this record |
|
|
|
|
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 |
|
|
|
Volume |
|
Issue |
|
Pages  |
870-874 |
|
|
Keywords |
|
|
|
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 |
|
Thesis |
|
|
|
Publisher |
|
Place of Publication |
|
Editor |
|
|
|
Language |
|
Summary Language |
|
Original Title |
|
|
|
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
|
Series Volume |
|
Series Issue |
|
Edition |
|
|
|
ISSN |
1520-5363 |
ISBN |
978-1-4577-1350-7 |
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
ICDAR |
|
|
Notes |
DAG |
Approved |
no |
|
|
Call Number |
Admin @ si @ LRL2011 |
Serial |
1790 |
|
Permanent link to this record |
|
|
|
|
Author |
Christophe Rigaud; Dimosthenis Karatzas; Joost Van de Weijer; Jean-Christophe Burie; Jean-Marc Ogier |

|
|
Title |
Automatic text localisation in scanned comic books |
Type |
Conference Article |
|
Year |
2013 |
Publication |
Proceedings of the International Conference on Computer Vision Theory and Applications |
Abbreviated Journal |
|
|
|
Volume |
|
Issue |
|
Pages  |
814-819 |
|
|
Keywords |
Text localization; comics; text/graphic separation; complex background; unstructured document |
|
|
Abstract |
Comic books constitute an important cultural heritage asset in many countries. Digitization combined with subsequent document understanding enable direct content-based search as opposed to metadata only search (e.g. album title or author name). Few studies have been done in this direction. In this work we detail a novel approach for the automatic text localization in scanned comics book pages, an essential step towards a fully automatic comics book understanding. We focus on speech text as it is semantically important and represents the majority of the text present in comics. The approach is compared with existing methods of text localization found in the literature and results are presented. |
|
|
Address |
Barcelona; February 2013 |
|
|
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 |
VISAPP |
|
|
Notes |
DAG; CIC; 600.056 |
Approved |
no |
|
|
Call Number |
Admin @ si @ RKW2013b |
Serial |
2261 |
|
Permanent link to this record |
|
|
|
|
Author |
Raul Gomez; Ali Furkan Biten; Lluis Gomez; Jaume Gibert; Marçal Rusiñol; Dimosthenis Karatzas |


|
|
Title |
Selective Style Transfer for Text |
Type |
Conference Article |
|
Year |
2019 |
Publication |
15th International Conference on Document Analysis and Recognition |
Abbreviated Journal |
|
|
|
Volume |
|
Issue |
|
Pages  |
805-812 |
|
|
Keywords |
transfer; text style transfer; data augmentation; scene text detection |
|
|
Abstract |
This paper explores the possibilities of image style transfer applied to text maintaining the original transcriptions. Results on different text domains (scene text, machine printed text and handwritten text) and cross-modal results demonstrate that this is feasible, and open different research lines. Furthermore, two architectures for selective style transfer, which means
transferring style to only desired image pixels, are proposed. Finally, scene text selective style transfer is evaluated as a data augmentation technique to expand scene text detection datasets, resulting in a boost of text detectors performance. Our implementation of the described models is publicly available. |
|
|
Address |
Sydney; Australia; September 2019 |
|
|
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 |
ICDAR |
|
|
Notes |
DAG; 600.129; 600.135; 601.338; 601.310; 600.121 |
Approved |
no |
|
|
Call Number |
GBG2019 |
Serial |
3265 |
|
Permanent link to this record |
|
|
|
|
Author |
Miquel Ferrer; Ernest Valveny |

|
|
Title |
Combination of OCR Engines for Page Segmentation based on Performance Evaluation |
Type |
Conference Article |
|
Year |
2007 |
Publication |
9th International Conference on Document Analysis and Recognition |
Abbreviated Journal |
|
|
|
Volume |
2 |
Issue |
|
Pages  |
784–788 |
|
|
Keywords |
|
|
|
Abstract |
|
|
|
Address |
Curitiba (Brazil) |
|
|
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 |
ICDAR |
|
|
Notes |
DAG |
Approved |
no |
|
|
Call Number |
DAG @ dag @ FeV2007 |
Serial |
838 |
|
Permanent link to this record |
|
|
|
|
Author |
Pau Riba; Josep Llados; Alicia Fornes |


|
|
Title |
Handwritten Word Spotting by Inexact Matching of Grapheme Graphs |
Type |
Conference Article |
|
Year |
2015 |
Publication |
13th International Conference on Document Analysis and Recognition ICDAR2015 |
Abbreviated Journal |
|
|
|
Volume |
|
Issue |
|
Pages  |
781 - 785 |
|
|
Keywords |
|
|
|
Abstract |
This paper presents a graph-based word spotting for handwritten documents. Contrary to most word spotting techniques, which use statistical representations, we propose a structural representation suitable to be robust to the inherent deformations of handwriting. Attributed graphs are constructed using a part-based approach. Graphemes extracted from shape convexities are used as stable units of handwriting, and are associated to graph nodes. Then, spatial relations between them determine graph edges. Spotting is defined in terms of an error-tolerant graph matching using bipartite-graph matching algorithm. To make the method usable in large datasets, a graph indexing approach that makes use of binary embeddings is used as preprocessing. Historical documents are used as experimental framework. The approach is comparable to statistical ones in terms of time and memory requirements, especially when dealing with large document collections. |
|
|
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 |
ICDAR |
|
|
Notes |
DAG; 600.077; 600.061; 602.006 |
Approved |
no |
|
|
Call Number |
Admin @ si @ RLF2015b |
Serial |
2642 |
|
Permanent link to this record |
|
|
|
|
Author |
Ruben Tito; Dimosthenis Karatzas; Ernest Valveny |


|
|
Title |
Document Collection Visual Question Answering |
Type |
Conference Article |
|
Year |
2021 |
Publication |
16th International Conference on Document Analysis and Recognition |
Abbreviated Journal |
|
|
|
Volume |
12822 |
Issue |
|
Pages  |
778-792 |
|
|
Keywords |
Document collection; Visual Question Answering |
|
|
Abstract |
Current tasks and methods in Document Understanding aims to process documents as single elements. However, documents are usually organized in collections (historical records, purchase invoices), that provide context useful for their interpretation. To address this problem, we introduce Document Collection Visual Question Answering (DocCVQA) a new dataset and related task, where questions are posed over a whole collection of document images and the goal is not only to provide the answer to the given question, but also to retrieve the set of documents that contain the information needed to infer the answer. Along with the dataset we propose a new evaluation metric and baselines which provide further insights to the new dataset and task. |
|
|
Address |
|
|
|
Corporate Author |
|
Thesis |
|
|
|
Publisher |
|
Place of Publication |
|
Editor |
|
|
|
Language |
|
Summary Language |
|
Original Title |
|
|
|
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
LNCS |
|
|
Series Volume |
|
Series Issue |
|
Edition |
|
|
|
ISSN |
|
ISBN |
|
Medium |
|
|
|
Area |
|
Expedition |
|
Conference |
ICDAR |
|
|
Notes |
DAG; 600.121 |
Approved |
no |
|
|
Call Number |
Admin @ si @ TKV2021 |
Serial |
3622 |
|
Permanent link to this record |