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BRAIN: Novel Ontologies-Based OCR – Error Correction Cooperating with Graph Component Extraction

The article written by Sarunya Kanjanawattana and Masaomi Kimura is a study about Optical Character Recognition (OCR), which represents a a typical tool used to transform image-based characters to computer editable characters. The two illustrate a novel method which is a combination of a graph componenet extraction and an OCR-error correction.

In the last years, graphs became very important to researches, as they contain significant information which can be extracted and used. Graphs offer data summarization which presents essential information that is interpreted by acquiring small descriptive details. In order to succeed in obtaining a primary interpretation, OCR was created, which is an approving solution used for acquiring graph components as a digital format o character letters.  This study uses a collection of bar graphs which contains at least axis descriptions and a legend in order to illustrate OCR.

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