Paper Info
Title
A Voting-Based Technique For Word Spotting In Handwritten Document Images
Abstract
Word spotting in handwritten document images is a field of immense interest due to its widespread applications. Recognition-free and recognition-based approaches are the two comprehensively studied regimes for the said problem out of which the first one is more realistic for practical applications. In literature, several works have been found that have used contour and distance-based measures for matching of the profiles of two word images. Although this is a prudent choice for printed words, the same often faces bottlenecks for unconstrained handwriting. To this end, this work applies dynamic time warping algorithm on logarithmic profiles of handwritten word images to lessen the uncontrolled profile variation that occurs due to elongation while writing some characters. We have considered both global and local interpretations of a word image by dividing it vertically into a number of sub-parts. This multi-view analysis provides close-up views of different approximations for the same word image. Finally, a voting scheme is evoked to produce the final decision. Besides, we have adopted a pruning method to pre-filter the target word images prior to applying the voting-based word matching scheme. The method has been tested on word images, taken from Qatar University Writer Identification database. We have obtained satisfactory results as compared to many state-of-the-art methods that also include deep learning-based feature extraction models.
Year
DOI
Venue
2021
10.1007/s11042-020-10363-0
MULTIMEDIA TOOLS AND APPLICATIONS
Keywords
DocType
Volume
Logarithmic profile, Keyword spotting, QUWI database, Multi-view, Dynamic time warping, Handwritten document
Journal
80
Issue
ISSN
Citations 
8
1380-7501
0
PageRank 
References 
Authors
0.34
0
5
Name
Order
Citations
PageRank
Shamik Majumder100.34
Subhrangshu Ghosh200.34
Samir Malakar3227.90
Ram Sarkar442068.85
Mita Nasipuri5725107.01