Development of an Automated Technique for Reconstructing Jawi Characters in Historical Documents
Zulcaffle, Tengku Mohd Afendi (2007) Development of an Automated Technique for Reconstructing Jawi Characters in Historical Documents. Masters thesis, Universiti Putra Malaysia.
The old documents in Jawi script are still being used widely for references. The quality of the hard copies of those scripts will be deteriorating as time passes. Manual reconstruction may take long time if the documents are sufficiently thick. The accuracy of the document image recognition algorithms is much dependent on the level of noise on the document. Therefore, the development of the historical Jawi character reconstruction algorithm is a significant contributions to the success of the old Jawi manuscript maintenance and recognition systems. The Background Subtraction technique has proved to be the best algorithm when historical document images were evaluated. The proposed technique has improved the algorithm by incorporating an autonomous decision making, that makes the binarization technique a scale invariant algorithm. The prefiltering and post processing will further enhance the ability of the algorithm to remove noise from the documents. In the post binarization algorithm, separation techniques between characters with holes and without holes is introduced in order for different morphological operations to be applied to those characters. This method will enhance connection between broken characters but still preserving the originality of the document. A noise model has been developed to test the reliability of the proposed algorithm. The model was developed based on several predefined criteria. The algorithms have been implemented using Matlab software version 6.5. The reliability of the proposed algorithms have been tested over simulated and real data. Comparison has been made between the Background Subtraction technique and the proposed method by manual inspection and mathematical evaluation. The results of the algorithms were mathematically evaluated using the Relative Foreground Area Error. Results have shown that better performance has been obtained using the proposed method. The framework managed to create historical Jawi characters more presentable. The system is not only applicable to historical Jawi characters, it can be easily adapted to any other historical characters in different languages.
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