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Script recognition--a review.

Debashis Ghosh¹, Tulika Dube, Adamane P Shivaprasad

¹Department of Electronics and Computer Engineering, Indian Institute of Technology Roorkee, Roorkee, India. ghoshfec@iitr.ernet.in

IEEE Transactions on Pattern Analysis and Machine Intelligence

|October 27, 2010

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See all related articles

Automatic script identification is crucial for document analysis in multilingual settings. This survey reviews structure-based and visual-appearance-based methods, highlighting the need for further research, especially for handwritten documents.

Area of Science:

Natural Language Processing
Computer Vision
Document Analysis

Background:

Multiscript and multilingual environments necessitate accurate script identification for effective document analysis.
Choosing appropriate character recognition and document analysis algorithms depends on knowing the document's script.

Purpose of the Study:

To provide a comprehensive overview of automatic script identification methodologies.
To categorize existing techniques into structure-based and visual-appearance-based approaches.

Main Methods:

Review and categorization of existing automatic script identification techniques.
Exploration of methods for online data and video-texts.

Main Results:

Related Experiment Videos

Existing methods are broadly classified into structure-based and visual-appearance-based techniques.

The survey covers script identification for various data types, including online and video-texts.

Conclusions:

The field of automatic script identification is relatively underdeveloped.
Further research is particularly needed for handwritten documents.