Thinning Chinese, Korean, Japanese and Thai script for segmentation-free OCRs

Abstract

While searching on the internet, the OCR keyword will return a thousand research papers on optical character recognition. These papers are ranging from Latin language scripts, Cyrillic, Devanagari, Korean, Japanese, Chinese and Arabic scripts. Sindhi and many other languages extend the Arabic script in which base characters are same while the other characters are adopted in a same situation. Many of the languages possess OCRs for their languages but still there are some other languages which still require the OCRs for their language. The paper is organized in various sections such as introduction followed by Sindhi language characteristics. The OCR approaches and methods are explained. The last section describes the conclusion and future work. An OCR is a set of complex steps to convert image text to editable text. Skeletonization or shrining a word or character body is a method which helps to recognize text more easily. Multiple languages impose various challenges and are hard to recognize and skeletonization or thinning produces a new image which can be easy to recognize. The connected elements are found with this approach. A custom-built software has been developed to interface the generalized thinning algorithm so that the scripts of Chinese, Japanese, Korean and Thai be tested. The output of this algorithm is the final image to be used for the further processing of the OCR. Although the intention was to create algorithms for segmentation free OCRs, the study results and the software can also be used for segmentation-based algorithms. The generalized algorithm shows the accuracy of more than 95% for the experimented four scripts.