DocumentCode
2504115
Title
Document Image Retrieval Using Feature Combination in Kernel Space
Author
Hassan, Ehtesham ; Chaudhury, Santanu ; Gopal, M.
Author_Institution
Dept. of Electr. Eng., IIT Delhi, Delhi, India
fYear
2010
fDate
23-26 Aug. 2010
Firstpage
2009
Lastpage
2012
Abstract
The paper presents application of multiple features for word based document image indexing and retrieval. A novel framework to perform Multiple Kernel Learning for indexing using the Kernel based Distance Based Hashing is proposed. The Genetic Algorithm based framework is used for optimization. Two different features representing the structural organization of word shape are defined. The optimal combination of both the features for indexing is learned by performing MKL. The retrieval results for document collection belonging to Devanagari script are presented.
Keywords
document image processing; file organisation; genetic algorithms; image retrieval; indexing; learning (artificial intelligence); Devanagari script; distance based hashing; document image retrieval; feature combination; genetic algorithm; kernel space; multiple kernel learning; word based document image indexing; Equations; Gallium; Histograms; Indexing; Kernel; Optimization; Shape; Document Indexing; Multiple Kernel Learning; Shape Descriptor;
fLanguage
English
Publisher
ieee
Conference_Titel
Pattern Recognition (ICPR), 2010 20th International Conference on
Conference_Location
Istanbul
ISSN
1051-4651
Print_ISBN
978-1-4244-7542-1
Type
conf
DOI
10.1109/ICPR.2010.495
Filename
5597259
Link To Document