Learning-based word spotting system for Arabic handwritten documents

作者：

Highlights：

• We propose a learning-based word spotting system for Arabic handwritten documents.

• The system is designed to address the lack of boundary problem in Arabic script.

• Pieces of Arabic Words (PAWs) are extracted from text lines.

• Language models are incorporated into the system to reconstruct words from PAWs.

• The system is tested on a variety of documents with promising results.

摘要

Highlights•We propose a learning-based word spotting system for Arabic handwritten documents.•The system is designed to address the lack of boundary problem in Arabic script.•Pieces of Arabic Words (PAWs) are extracted from text lines.•Language models are incorporated into the system to reconstruct words from PAWs.•The system is tested on a variety of documents with promising results.

论文关键词：Arabic handwriting recognition,Language models,Word spotting,Partial segmentation

论文评审过程：Available online 11 September 2013.

论文官网地址：https://doi.org/10.1016/j.patcog.2013.08.014