Offline Writer Identification Using Local Derivative Pattern

In this paper, we propose a scheme for identifying the authorship of off-line handwritten documents based on a histogram-based descriptor. The idea of our work is inspired from that of the Local Derivative Patterns (LDP), that has found much success in the application of face recognition. However, t...

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Bibliographic Details
Main Authors: Kanetkar, Salil, Pathania, Ayush, Venugopal, Vivek, Sundaram, Suresh
Format: Conference Proceeding
Language:English
Subjects:
CVL Database
Face recognition
Feature extraction
Histograms
Local Binary Pattern
Local Derivative Patterns
Offline text independent writer identification
Proposals
Training
Writing
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Summary:In this paper, we propose a scheme for identifying the authorship of off-line handwritten documents based on a histogram-based descriptor. The idea of our work is inspired from that of the Local Derivative Patterns (LDP), that has found much success in the application of face recognition. However, to the best of our knowledge, this work is the first of its kind that utilizes them for characterizing the writing style of an author. The efficacy of the algorithm has been tested on the handwritten documents of the CVL database, using two strategies. The performance of writer identification rate on this database indicate that the proposed descriptor is effective for the problem of text independent off-line writer identification.
ISSN:2167-6445
DOI:10.1109/ICFHR.2016.0073