모바일 시스템에서 텍스트 인식 위한 적응적 문자 분할

• 영문명: Adaptive Character Segmentation to Improve Text Recognition Accuracy on Mobile Phones
• 발행기관: 한국스마트미디어학회
• 저자명: 김정식(Jeong Sik Kim) 양형정(Hyung Jeog Yang) 김수형(Soo Hyung Kim) 이귀상(Guee sang Lee) Luu Ngoc Do 김선희(Sun Hee Kim)
• 간행물 정보: 『스마트미디어저널』Vol1, No.4, 59~71쪽, 전체 13쪽
• 주제분류: 공학 > 컴퓨터학
• 파일형태: PDF
• 발행일자: 2012.12.30

영문 초록

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.

목차

Abstract

I. Introduction

II. Related Work

III. Proposed Method

IV. Experimental Result

V. Conclusion

References

키워드

Text Recognition Segmentation Printed Letter Handwritten Letter