Result: Word image retrieval using binary features
Title:
Word image retrieval using binary features
Authors:
Source:
Document recognition and retrieval XI (San Jose CA, 21-22 January 2004)SPIE proceedings series. 5296:45-53
Publisher Information:
Bellingham WA: SPIE, 2004.
Publication Year:
2004
Physical Description:
print, 12 ref
Original Material:
INIST-CNRS
Subject Terms:
Documentation, Electronics, Electronique, Optics, Optique, Physics, Physique, Telecommunications, Télécommunications, Sciences exactes et technologie, Exact sciences and technology, Sciences et techniques communes, Sciences and techniques of general use, Sciences de l'information. Documentation, Information science. Documentation, Systèmes de recherche d'informations. Système de gestion documentaire et d'information, Information retrieval systems. Information and document management system, Interfaces. Logiciels, Interfaces. Software, Sciences de l'information et de la communication, Information and communication sciences, Système de recherche documentaire. Système de gestion documentaire et d'information, Algorithme, Algorithm, Algoritmo, Recherche information, Information retrieval, Búsqueda información, Document numérisé, Digitized document, Ecriture, Writing, Image de mots, Recherche d'image, Image retrieval
Document Type:
Conference
Conference Paper
File Description:
text
Language:
English
Author Affiliations:
Departments of Human Genetics and Biostatistics, School of Medicine, UCLA, 695 Charles E. Young Drive South, Los Angeles, CA 90095-7088, United States
CEDAR, Computer Science and Engineering Department, State University of New York at Buffalo, Buffalo, NY 14228, United States
CEDAR, Computer Science and Engineering Department, State University of New York at Buffalo, Buffalo, NY 14228, United States
Rights:
Copyright 2004 INIST-CNRS
CC BY 4.0
Sauf mention contraire ci-dessus, le contenu de cette notice bibliographique peut être utilisé dans le cadre d’une licence CC BY 4.0 Inist-CNRS / Unless otherwise stated above, the content of this bibliographic record may be used under a CC BY 4.0 licence by Inist-CNRS / A menos que se haya señalado antes, el contenido de este registro bibliográfico puede ser utilizado al amparo de una licencia CC BY 4.0 Inist-CNRS
CC BY 4.0
Sauf mention contraire ci-dessus, le contenu de cette notice bibliographique peut être utilisé dans le cadre d’une licence CC BY 4.0 Inist-CNRS / Unless otherwise stated above, the content of this bibliographic record may be used under a CC BY 4.0 licence by Inist-CNRS / A menos que se haya señalado antes, el contenido de este registro bibliográfico puede ser utilizado al amparo de una licencia CC BY 4.0 Inist-CNRS
Notes:
Sciences of information and communication. Documentation
FRANCIS
FRANCIS
Accession Number:
edscal.16075825
Database:
PASCAL Archive
Further Information
Existing word image retrieval algorithms suffer from either low retrieval precision or high computation complexity. We present an effective and efficient approach for word image matching by using gradient-based binary features. Experiments over a large database of handwritten word images show that the proposed approach consistently outperforms the existing best handwritten word image retrieval algorithm, Dynamic Time Warping (DTW) with profile-based shape features. Not only does the proposed approach have much higher retrieval accuracy, but also it is 893 times faster than DTW.