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
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;
Conference_Titel :
Pattern Recognition (ICPR), 2010 20th International Conference on
Conference_Location :
Istanbul
Print_ISBN :
978-1-4244-7542-1
DOI :
10.1109/ICPR.2010.495