An HMM-Based Approach for Off-Line Unconstrained Handwritten Word Modeling and Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
Using HMM Based Recognizers for Writer Identification and Verification
IWFHR '04 Proceedings of the Ninth International Workshop on Frontiers in Handwriting Recognition
Automatic Writer Identification Using Fragmented Connected-Component Contours
IWFHR '04 Proceedings of the Ninth International Workshop on Frontiers in Handwriting Recognition
A Comparison of Clustering Methods for Writer Identification and Verification
ICDAR '05 Proceedings of the Eighth International Conference on Document Analysis and Recognition
A writer identification and verification system
Pattern Recognition Letters
Writer identification forensic system based on support vector machines with connected components
IEA/AIE'2004 Proceedings of the 17th international conference on Innovations in applied artificial intelligence
Off-lineWriter Identification Using Gaussian Mixture Models
ICPR '06 Proceedings of the 18th International Conference on Pattern Recognition - Volume 03
Pattern Recognition Letters
A writer identification and verification system using HMM based recognizers
Pattern Analysis & Applications
Text-Independent Writer Identification and Verification Using Textural and Allographic Features
IEEE Transactions on Pattern Analysis and Machine Intelligence
Text-Independent Writer Identification and Verification on Offline Arabic Handwriting
ICDAR '07 Proceedings of the Ninth International Conference on Document Analysis and Recognition - Volume 02
A New Method for Writer Identification and Verification Based on Farsi/Arabic Handwritten Texts
ICDAR '07 Proceedings of the Ninth International Conference on Document Analysis and Recognition - Volume 02
Writer Identification in Old Handwritten Music Scores
DAS '08 Proceedings of the 2008 The Eighth IAPR International Workshop on Document Analysis Systems
Text-independent Persian Writer Identification Using Fuzzy Clustering Approach
ICIME '09 Proceedings of the 2009 International Conference on Information Management and Engineering
Combining Contour Based Orientation and Curvature Features for Writer Recognition
CAIP '09 Proceedings of the 13th International Conference on Computer Analysis of Images and Patterns
A Set of Chain Code Based Features for Writer Recognition
ICDAR '09 Proceedings of the 2009 10th International Conference on Document Analysis and Recognition
On the Use of Textural Features for Writer Identification in Old Handwritten Music Scores
ICDAR '09 Proceedings of the 2009 10th International Conference on Document Analysis and Recognition
FHT: An Unconstraint Farsi Handwritten Text Database
ICDAR '09 Proceedings of the 2009 10th International Conference on Document Analysis and Recognition
An Efficient Method for Offline Text Independent Writer Identification
ICPR '10 Proceedings of the 2010 20th International Conference on Pattern Recognition
Writer identification using directional ink-trace width measurements
Pattern Recognition
Handwriting recognition accuracy improvement by author identification
ICAISC'06 Proceedings of the 8th international conference on Artificial Intelligence and Soft Computing
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In this paper, an efficient method for text-independent writer identification using a codebook method is proposed. The method uses the occurrence histogram of the shapes in a codebook to create a feature vector for each specific manuscript. For cursive handwritings, a wide variety of different shapes exist in the connected components obtained from the handwriting. Small fragments of connected components are used to avoid complex patterns. Two efficient methods for extracting codes from contours are introduced. One method uses the actual pixel coordinates of contour fragments while the other one uses a linear piece-wise approximation using segment angles and lengths. To evaluate the methods, writer identification is conducted on two English and three Farsi handwriting databases. Both methods show promising performances with the performance of second method being better than the first one.