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Adaptive Character Segmentation to Improve Text Recognition Accuracy on Mobile Phones
김정식,양형정,김수형,이귀상,김선희,Kim, Jeong Sik,Yang, Hyung Jeong,Kim, Soo Hyung,Lee, Guee Sang,Do, Luu Ngoc,Kim, Sun Hee THE KOREAN INSTITUTE OF SMART MEDIA 2012 스마트미디어저널 Vol.1 No.4
Since mobile phones are used as common communication devices, their applications are increasingly important to human's life. Using smart-phones camera to collect daily life environment's information is one of targets for many applications such as text recognition, object recognition or context awareness. Studies have been conducted to provide important information through the recognition of texts, which are artificially or naturally included in images and movies acquired from mobile phones. In this study, a character segmentation method that improves character-recognition accuracy in images obtained from mobile phone cameras is proposed. The proposed method first classifies texts in a given image to printed letters and handwritten letters since segmentation approaches for them are different. For printed letters, rough segmentation process is conducted, then the segmented regions are integrated, deleted, and re-segmented. Segmentation for the handwritten letters is performed after skews are corrected and the characters are classified by integrating them. The experimental result shows our method achieves a successful performance for both printed and handwritten letters as 95.9% and 84.7%, respectively.