• Journal of Intelligence and Information Systems
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• v.8 no.1
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• pp.27-39
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• 2002

A locating text technique capable of locating and extracting text blocks in various Web images is presented here. Until now this area of work has been ignored by researchers even if this sort of text may be meaningful for internet users. The algorithms associated with the technique work without prior knowledge of the text orientation, size or font. In the work presented in this research, our text extraction algorithm utilizes useful edge detection followed by histogram analysis on the genuine characteristics of letters defined by text clustering region, to properly perform extraction of the text region that does not depend on font styles and sizes. By a number of experiments we have showed impressively acceptable results.

• The Transactions of the Korea Information Processing Society
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• v.3 no.2
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• pp.348-358
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• 1996

If a method of character region extraction will have general purposes, it could not but make use of common features which all target images have. This paper suggests these common features should be considered as the coalitions for the region to be extracted within a framework of the cost minimization. The method suggested above could be effective by minimizing a cost function estmating the extent that character regions satify quantitatively the features, through Simulated Annealing Method. This method has an uniqueness in that it defines the cost function. Experimental result verify the usefulness of this cost minimization approach to characer region extraction.

• Proceedings of the Korea Multimedia Society Conference
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• 1998.04a
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• pp.138-142
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• 1998

자동차 번호판 인식시스템은 영상획득, 번호판 추출, 전처리(이치화), 문자영역분할, 문자인식 등의 5가지 핵심부분으로 구성되어 있다. 따라서 자동차 번호판 인식시스템의 최종 인식률은 각 단계의 성능에 따라 직접적인 영향을 받는다. 본 논문은 컴퓨터 비젼의 한 분야인 영상처리 기법을 이용한 이치화된 자동차 번호판의 문자영역 추출에 관한 연구로서 문자 인식단계에서 높은 인식률을 확보하기 위해서 가장 중요한 입력 데이터의 상태를 보다 깨끗하게 정확하게 분리하는데 변형된 Run Length Coding 기법을 이용하여 효과적이고 빠른 문자 영역 분리 방법을 제안함으로서 처리속도의 향상은 물론 잡영에도 강한 문자 영역 분리 시스템을 구현하였다.

• The KIPS Transactions:PartB
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• v.12B no.4 s.100
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• pp.369-378
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• 2005

Document image is segmented and classified into text, picture, or table by a document layout analysis, and the words in table regions are significant for keyword spotting because they are more meaningful than the words in other regions. This paper proposes a method to extract words from table regions in document images. As word extraction from table regions is practically regarded extracting words from cell regions composing the table, it is necessary to extract the cell correctly. In the cell extraction module, table frame is extracted first by analyzing connected components, and then the intersection points are extracted from the table frame. We modify the false intersections using the correlation between the neighboring intersections, and extract the cells using the information of intersections. Text regions in the individual cells are located by using the connected components information that was obtained during the cell extraction module, and they are segmented into text lines by using projection profiles. Finally we divide the segmented lines into words using gap clustering and special symbol detection. The experiment performed on In table images that are extracted from Korean documents, and shows $99.16\%$ accuracy of word extraction.

• Proceedings of the Korean Society of Computer Information Conference
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• 2010.07a
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• pp.125-127
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• 2010

본 논문에서는 동영상에서 비교적 단일 색상의 배경과 문자를 갖는 캡션을 문자인식을 위하여 문자와 배경간의 명암값 결정에 관한 내용이다. 먼저 캡션에 대해 그레이 스케일로 전환을 한 후, Otsu 방법[1]을 이용하여 이진화를 수행한다. 이 후 이진화 영상에서 흰색영역 검은색영역에 대해 각각 최대 내접 정사각형을 산출한다. 다음으로 각각의 영역에서 산출된 최대 내접 정사각형의 분산의 대소를 비교하여 문자영역과 배경영역을 결정한다. 이후 전역적인 잡음을 제거하기 문자영역에 대해 Otsu 방법을 이용하여 최종 문자영역을 결정한다. 제안된 방법의 문자영역의 명암값 결정 정확도는 약 99%로 매우 우수한 성능을 보였다.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.45 no.3
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• pp.12-19
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• 2008

Detection of a number plate consists of three stages; division of a number plate, extraction of each character from the plate, recognition of the characters. Among of these three states, division stage of a number plate is the most important part and also the most time-consuming state. This paper suggests an effective region extraction method of a number plate for various images obtained from unmanned inspection systems of illegal parking violation, especially when we have to consider the diverse surrounding environments of roads. Our approaching method detects each region by investigating the characteristics in changes of brightness and intensity between the background part and character part, and the characteristics on character parts such as the sizes, heights, widths, and distance in between two characters. The method also divides a number plate into different types of the plate. This research can solve the number plate region detection failure problems caused by plate edge damages not only for Korean domestic number plates but also for new European style number plates. The method also reduces the time consumption by processing the detection in real-time, therefore, it can be used as a practical solution.

• Proceedings of the Korea Information Processing Society Conference
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• 2003.11a
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• pp.275-278
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• 2003

자동차 번호판 인식 시스템은 영상획득, 번호판추출, 전처리(이진화), 문자영역 분할, 문자인식 등의 5가지 핵심 부분으로 구성된다. 따라서 자동차 번호판 인식 시스템의 최종 인식율은 각 단계의 성능에 따라 직접적인 영향을 받는다. 본 논문은 영상처리 기법을 이용하여 영상에서 번호판 영역을 추출을 위한 연구로 문자인식 단계에서 높은 인식율을 확보할 수 있도록 빠른 연산속도와 추출 정확성을 높일 수 있는 알고리즘을 제안한다.

• Journal of Intelligence and Information Systems
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• v.8 no.1
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• pp.15-25
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• 2002

This paper proposes a vehicle license plate recognition system, which has relatively a simple structure and is highly tolerant of noise, by using the DCT(Discrete Cosine Transform) coefficients extracted from the character region of a license plate and the LVQ(Learning Vector Quantization) neural network. The image of a license plate is taken from a captured vehicle image based on RGB color information, and the character region is derived by the histogram of the license plate and the relative position of individual characters in the plate. The feature vector obtained by the DCT of extracted character region is utilized as an input to the LVQ neural classifier fur the recognition process. In the experiment, 109 vehicle images captured under various types of circumstances were tested with the proposed method, and the relatively high extraction rate of license plates and recognition rate were achieved.

• Proceedings of the KAIS Fall Conference
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• 2006.11a
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• pp.220-224
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• 2006

The text to be included in the natural images has many important information in the natural image. Therefore, if we can extract the text in natural images, It can be applied to many important applications. In this paper, we propose a text region extraction method using pattern histogram of character-edge map. We extract the edges with the Canny edge detector and creates 16 kind of edge map from an extracted edges. And then we make a character-edge map of 8 kinds that have a character feature with a combination of an edge map. We extract text region using 8 kinds of character-edge map and 16 kind of edge map. Verification of text candidate region uses analysis of a character-edge map pattern histogram and structural feature of text region. The method to propose experimented with various kind of the natural images. The proposed approach extracted text region from a natural images to have been composed of a complex background, various letters, various text colors effectively.

• Proceedings of the KAIS Fall Conference
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• 2011.05a
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• pp.396-399
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• 2011

모바일 기기의 보급이 확대됨으로서 모바일 기기에 내장된 카메라로 획득한 영상을 처리하는 다양한 종류의 응용프로그램이 개발되어 사용되고 있다. 대표적인 응용프로그램은 카메라로 찍은 영상의 사물 검색결과를 인터넷 검색엔진과 연계함으로서 키워드 입력 없이 검색할 수 있도록 하는 것이다. 본 연구는 그 중에서 한글 문자가 포함된 영상을 대상으로 영상검색 수행하는 연구로서 영상에서 한글 문자 영역을 검출하는 방법을 제안하였다. 한글 문자 구조 특징으로 한글 자소를 병합하여 후보 문자 영역을 추출하고 병합된 후보 문자 영역을 한글 6가지 문자 유형 특징을 기반으로 문자 영역을 여부를 판별함으로서 최종적인 문자 영역을 검출한다. 실험결과 문자영역 재현률이 향상됨을 알 수 있었다.