Multi-oriented and multi-scaled text character analysis and recognition in graphical documents and their applications to document image retrieval

With the advent research of Document Image Analysis and Recognition (DIAR), an important line of research is explored on indexing and retrieval of graphics rich docu- ments. It aims at nding relevant documents relying on segmentation and recognition of text and graphics components underlying in non-...

ver descrição completa

Detalhes bibliográficos
Autor: Roy, Partha Pratim
Tipo de documento: tese
Data de publicação:2011
País:España
Recursos:Universitat Autònoma de Barcelona
Repositório:Dipòsit Digital de Documents de la UAB
Idioma:inglês
OAI Identifier:oai:ddd.uab.cat:99226
Acesso em linha:https://ddd.uab.cat/record/99226
Access Level:Acceso aberto
Palavra-chave:Reconeixement de formes (Informàtica)
Recuperació d'imatges per contingut
Reconeixement òptic de caràcters
id ES_d9ee38e470e6ac7e379c868169e2ebb2
oai_identifier_str oai:ddd.uab.cat:99226
network_acronym_str ES
network_name_str España
repository_id_str
spelling Multi-oriented and multi-scaled text character analysis and recognition in graphical documents and their applications to document image retrievalRoy, Partha PratimReconeixement de formes (Informàtica)Recuperació d'imatges per contingutReconeixement òptic de caràctersWith the advent research of Document Image Analysis and Recognition (DIAR), an important line of research is explored on indexing and retrieval of graphics rich docu- ments. It aims at nding relevant documents relying on segmentation and recognition of text and graphics components underlying in non-standard layout where commercial OCRs can not be applied due to complexity. This thesis is focused towards text infor- mation extraction approaches in graphical documents and retrieval of such documents using text information. Automatic text recognition in graphical documents (map, engineering drawing, etc.) involves many challenges because text characters are usually printed in multi- oriented and multi-scale way along with di erent graphical objects. Text characters are used to annotate the graphical curve lines and hence, many times they follow curvi-linear paths too. For OCR of such documents, individual text lines and their corresponding words/characters need to be extracted. For recognition of multi-font, multi-scale and multi-oriented characters, we have proposed a feature descriptor for character shape using angular information from con- tour pixels to take care of the invariance nature. To improve the e ciency of OCR, an approach towards the segmentation of multi-oriented touching strings into individual characters is also discussed. Convex hull based background information is used to segment a touching string into possible primitive segments and later these primitive segments are merged to get optimum segmentation using dynamic programming. To overcome the touching/overlapping problem of text with graphical lines, a character spotting approach using SIFT and skeleton information is included. Afterwards, we propose a novel method to extract individual curvi-linear text lines using the fore- ground and background information of the characters of the text and a water reservoir concept is used to utilize the background information. We have also formulated the methodologies for graphical document retrieval ap- plications using query words and seals. The retrieval approaches are performed using recognition results of individual components in the document. Given a query text, the system extracts positional knowledge from the query word and uses the same to generate hypothetical locations in the document. Indexing of documents is also per- formed based on automatic detection of seals from documents containing cluttered background. A seal is characterized by scale and rotation invariant spatial feature descriptors computed from labelled text characters and a concept based on the Generalized Hough Transform is used to locate the seal in documents. Keywords: Document Image Analysis, Graphics Recognition, Dynamic Pro- gramming, Generalized Hough Transform, Character Recognition, Touching Charac- ter Segmentation, Text/Graphics Separation, Curve-Line Separation, Word Retrieval, Seal Detection and Recognition.Universitat Autònoma de BarcelonaUniversitat Autònoma de Barcelona. Departament de Ciències de la ComputacióLladós, JosepPal, Umapada 22011-01-0120112011-01-01Tesi doctoralhttp://purl.org/coar/resource_type/c_db06VoRhttp://purl.org/coar/version/c_970fb48d4fbd8a85info:eu-repo/semantics/doctoralThesisapplication/pdfhttps://ddd.uab.cat/record/99226reponame:Dipòsit Digital de Documents de la UABinstname:Universitat Autònoma de BarcelonaInglésengopen accesshttp://purl.org/coar/access_right/c_abf2Aquest material està protegit per drets d'autor i/o drets afins. Podeu utilitzar aquest material en funció del que permet la legislació de drets d'autor i drets afins d'aplicació al vostre cas. Per a d'altres usos heu d'obtenir permís del(s) titular(s) de drets.https://rightsstatements.org/vocab/InC/1.0/info:eu-repo/semantics/openAccessoai:ddd.uab.cat:992262026-06-06T12:50:31Z
dc.title.none.fl_str_mv Multi-oriented and multi-scaled text character analysis and recognition in graphical documents and their applications to document image retrieval
title Multi-oriented and multi-scaled text character analysis and recognition in graphical documents and their applications to document image retrieval
spellingShingle Multi-oriented and multi-scaled text character analysis and recognition in graphical documents and their applications to document image retrieval
Roy, Partha Pratim
Reconeixement de formes (Informàtica)
Recuperació d'imatges per contingut
Reconeixement òptic de caràcters
title_short Multi-oriented and multi-scaled text character analysis and recognition in graphical documents and their applications to document image retrieval
title_full Multi-oriented and multi-scaled text character analysis and recognition in graphical documents and their applications to document image retrieval
title_fullStr Multi-oriented and multi-scaled text character analysis and recognition in graphical documents and their applications to document image retrieval
title_full_unstemmed Multi-oriented and multi-scaled text character analysis and recognition in graphical documents and their applications to document image retrieval
title_sort Multi-oriented and multi-scaled text character analysis and recognition in graphical documents and their applications to document image retrieval
dc.creator.none.fl_str_mv Roy, Partha Pratim
author Roy, Partha Pratim
author_facet Roy, Partha Pratim
author_role author
dc.contributor.none.fl_str_mv Universitat Autònoma de Barcelona. Departament de Ciències de la Computació
Lladós, Josep
Pal, Umapada
dc.subject.none.fl_str_mv Reconeixement de formes (Informàtica)
Recuperació d'imatges per contingut
Reconeixement òptic de caràcters
topic Reconeixement de formes (Informàtica)
Recuperació d'imatges per contingut
Reconeixement òptic de caràcters
description With the advent research of Document Image Analysis and Recognition (DIAR), an important line of research is explored on indexing and retrieval of graphics rich docu- ments. It aims at nding relevant documents relying on segmentation and recognition of text and graphics components underlying in non-standard layout where commercial OCRs can not be applied due to complexity. This thesis is focused towards text infor- mation extraction approaches in graphical documents and retrieval of such documents using text information. Automatic text recognition in graphical documents (map, engineering drawing, etc.) involves many challenges because text characters are usually printed in multi- oriented and multi-scale way along with di erent graphical objects. Text characters are used to annotate the graphical curve lines and hence, many times they follow curvi-linear paths too. For OCR of such documents, individual text lines and their corresponding words/characters need to be extracted. For recognition of multi-font, multi-scale and multi-oriented characters, we have proposed a feature descriptor for character shape using angular information from con- tour pixels to take care of the invariance nature. To improve the e ciency of OCR, an approach towards the segmentation of multi-oriented touching strings into individual characters is also discussed. Convex hull based background information is used to segment a touching string into possible primitive segments and later these primitive segments are merged to get optimum segmentation using dynamic programming. To overcome the touching/overlapping problem of text with graphical lines, a character spotting approach using SIFT and skeleton information is included. Afterwards, we propose a novel method to extract individual curvi-linear text lines using the fore- ground and background information of the characters of the text and a water reservoir concept is used to utilize the background information. We have also formulated the methodologies for graphical document retrieval ap- plications using query words and seals. The retrieval approaches are performed using recognition results of individual components in the document. Given a query text, the system extracts positional knowledge from the query word and uses the same to generate hypothetical locations in the document. Indexing of documents is also per- formed based on automatic detection of seals from documents containing cluttered background. A seal is characterized by scale and rotation invariant spatial feature descriptors computed from labelled text characters and a concept based on the Generalized Hough Transform is used to locate the seal in documents. Keywords: Document Image Analysis, Graphics Recognition, Dynamic Pro- gramming, Generalized Hough Transform, Character Recognition, Touching Charac- ter Segmentation, Text/Graphics Separation, Curve-Line Separation, Word Retrieval, Seal Detection and Recognition.
publishDate 2011
dc.date.none.fl_str_mv 2
2011-01-01
2011
2011-01-01
dc.type.none.fl_str_mv Tesi doctoral
http://purl.org/coar/resource_type/c_db06
VoR
http://purl.org/coar/version/c_970fb48d4fbd8a85
dc.type.openaire.fl_str_mv info:eu-repo/semantics/doctoralThesis
format doctoralThesis
dc.identifier.none.fl_str_mv https://ddd.uab.cat/record/99226
url https://ddd.uab.cat/record/99226
dc.language.none.fl_str_mv Inglés
eng
language_invalid_str_mv Inglés
language eng
dc.rights.none.fl_str_mv open access
http://purl.org/coar/access_right/c_abf2
https://rightsstatements.org/vocab/InC/1.0/
dc.rights.openaire.fl_str_mv info:eu-repo/semantics/openAccess
rights_invalid_str_mv open access
http://purl.org/coar/access_right/c_abf2
https://rightsstatements.org/vocab/InC/1.0/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Universitat Autònoma de Barcelona
publisher.none.fl_str_mv Universitat Autònoma de Barcelona
dc.source.none.fl_str_mv reponame:Dipòsit Digital de Documents de la UAB
instname:Universitat Autònoma de Barcelona
instname_str Universitat Autònoma de Barcelona
reponame_str Dipòsit Digital de Documents de la UAB
collection Dipòsit Digital de Documents de la UAB
repository.name.fl_str_mv
repository.mail.fl_str_mv
_version_ 1869421481172140032
score 15,301603

Registros relacionados