• Journal of KIISE:Software and Applications
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• v.30 no.10
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• pp.904-911
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• 2003

In this paper, we propose an effective method for the distinction between machine-printed and handwritten Korean address images. It is important to know whether an input image is handwritten or machine-printed, because methods for handwritten image are quite different from those of machine-printed image in such applications as address reading, form processing, FAX routing, and so on. Our method consists of three blocks: valid connected components grouping, feature extraction, and classification. Features related to width and position of groups of valid connected components are used for the classification based on a neural network. The experiment done with live Korean address images has demonstrated the superiority of the proposed method. The correct classification rate for 3,147 testing images was about 98.85%.

• Journal of KIISE:Software and Applications
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• v.31 no.1
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• pp.8-19
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• 2004

In this paper, we propose an efficient method for locating destination address block on both of machine-Printed and handwritten Korean mail piece images. The proposed method extracts connected components from the binary mail piece image, generates text lines by merging them, and then groups the text fines into nine clusters. The destination address block is determined by selecting some clusters. Considering the geometric characteristics of address information on Korean mail piece, we split a mail piece image into nine areas with an equal size. The nine clusters are initialized with the center coordinate of each area. A modified Manhattan distance function is used to compute the distance between text lines and clusters. We modified the distance function on which the aspect ratio of mail piece could be reflected. The experiment done with live Korean mail piece images has demonstrated the superiority of the Proposed method. The success rate for 1, 988 testing images was about 93.56%.

• Proceedings of the Korean Information Science Society Conference
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• 2003.10b
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• pp.532-534
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• 2003

본 논문에서는 인쇄체 우편주소 영상에서 smearing과 히스토그램 분석을 이용한 고속의 문자열 기울기 보정 및 분할 방법을 제안하였다. 제안한 방법에서는 입력 영상을 가분할 하고, 각각의 가분할 영상에 대한 수평 히스토그램을 분석하여 기울기 측정 및 보정을 수행하였다. 문자열 분할 단계에서는, 기울기가 보정된 영상에 smearing을 수행하고, 영상에 존재하는 잡영 및 각종 바코드를 제거하고, 수평 히스토그램 분석을 통해 최종 문자열 분할 결과를 도출하였다. 제안한 방법을 사용한 실험에서 2,000 장의 테스트 영상 중 1,989장의 영상에서 정확한 문자분할 결과를 얻을 수 있었으며, 제안한 방법이 유효함을 보였다.

• The Transactions of the Korea Information Processing Society
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• v.6 no.10
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• pp.2563-2573
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• 1999

In most mail automatic processing centers, after facing and canceling, letter mails are passed through an Optical Character Recognition/Barcode Sorter(OCR/BS) to read the postal code and 3 of 5 fluorescent (luminescent) barcode is applied. Normally, 31%∼35% of this mails are rejected. The main reasons for reading failures are poor printing quality of addresses and barcodes, script printing, writing in a cursive hand, variety fonts, and failure to locate the address. Our goal is to provide mailer with top quality service and customer barcode service as we move toward 100% barcoding automation of letter mail. In this paper, we propose a method of printing 3 of 5 customer barcode, postal code management, and detection of postal code based on postal address for increase the performance of automatic processing system in mail items. Using postal code generating rules, which are automatically extracted from postal addresses and address numbers, creates postal codes. The customer barcode support system is implemented by C++ language and runs on IBM PC under Windows 95.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.18 no.9
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• pp.1358-1367
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• 1993

In this paper, OMR system based on image processing is developed which improve the performance of conventional OMR system based on line-scan method. Based on this OMR system, real-time OCR system which recognizes alphanumerics is also developed. We propose the OMCR system which recognize the mark and numerals at the same time. Besides, we improve the input system using constrained 7-segment type handwritten numeral instead of mark to solve the problem caused by miswriting the mark. In summary, we verified the reai-time recognition performance of developed OMCR system using application form for admission, answer sheet for college entrance examination and receipt sheet.

• Journal of Intelligence and Information Systems
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• v.10 no.3
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• pp.1-10
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• 2004

In this paper, a new character segmentation algorithm of machine printed character recognition is proposed. The new approach of the proposed character segmentation algorithm overcomes the weak points of both feature-based approaches and recognition-based approaches in character segmentation. This paper defines side profiles of touching characters. The character segmentation algorithm gives a candidate single character in touching characters by side profiles, without any help of character recognizer. It segments touching characters and decides the candidate single character by side profiles. This paper also defines cutting cost, which makes the proposed character segmentation find an optimal segmenting path. The performance of the proposed character segmentation algorithm in this paper has been obtained using a real envelope reader system, which can recognize addresses in U.S. mail pieces and sort the mail pieces. 3359 mail pieces were tested. The improvement was from $68.92\%\;to\;80.08\%$ by the proposed character segmentation.