Please use this identifier to cite or link to this item: https://scholarhub.balamand.edu.lb/handle/uob/835
Title: Stroke width exploitation to improve automatic recognition of Arabic handwritten texts
Authors: Chammas, Edgar
Likforman-Sulem, Laurence
Mokbel, Chafic 
Affiliations: Department of Electrical Engineering 
Keywords: Conferences
Manganese
Issue Date: 2017
Part of: 2017 1st International Workshop on Arabic Script Analysis and Recognition (ASAR)
Start page: 74
End page: 78
Conference: International Workshop on Arabic Script Analysis and Recognition (ASAR) (1st : 3-5 April 2017 : Nancy, France) 
Abstract: 
Several inherent factors increase the complexity of automatic recognition of handwritten documents, such as the size of writing and the stroke width. In a previous work [1], we showed that a successful exploitation of the writing size improves the recognition performance. In this work we are interested in considering the stroke width as a factor in modeling, to improve the performance of automatic systems. The experiments were conducted on Arabic handwritten documents from one of the largest labeled Arabic handwriting databases, NIST-OpenHaRT. The database includes large variability in the stroke width. We propose several approaches to deal with these changes in both training and recognition phases. The first experiments show that the recognition is largely affected by the stroke width. To account for this parameter, we propose to classify data into three classes according to the stroke width. In the recognition phase, we have thickened each text-line image into several versions with predefined values, then we combined the recognition scores for each value. This approach has significant performance gains for both an HMM-based and a BLSTM-based recognition systems. In addition, we integrated synthetic data to adapt HMM models at different stroke width measures. We also obtained performance gains by two different combination methods (ROVER, trellis) on the adapted models results. We provide the obtained recognition results showing the benefits of exploiting the stroke width, and compare them with a known approach for stroke width normalization.
URI: https://scholarhub.balamand.edu.lb/handle/uob/835
Ezproxy URL: Link to full text
Type: Conference Paper
Appears in Collections:Department of Electrical Engineering

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