• 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.

• 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.

• The KIPS Transactions:PartB
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• v.9B no.3
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• pp.375-382
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• 2002

Handwritten character recognition is classified into on-line handwritten character recognition and off-line handwritten character recognition. On-line handwritten character recognition has made a remarkable outcome compared to off-line hacdwritten character recognition. This method can acquire the dynamic written information such as the writing order and the position of a stroke by means of pen-based electronic input device such as a tablet board. On the contrary, Any dynamic information can not be acquired in off-line handwritten character recognition since there are extreme overlapping between consonants and vowels, and heavily noisy images between strokes, which change the recognition performance with the result of the preprocessing. This paper proposes a method that effectively extracts the stroke including dynamic information of characters for off-line Korean handwritten character recognition. First of all, this method makes improvement and binarization of input handwritten character image as preprocessing procedure using watershed algorithm. The next procedure is extraction of skeleton by using the transformed Lu and Wang's thinning: algorithm, and segment pixel array is extracted by abstracting the feature point of the characters. Then, the vectorization is executed with a maximum permission error method. In the case that a few strokes are bound in a segment, a segment pixel array is divided with two or more segment vectors. In order to reconstruct the extracted segment vector with a complete stroke, the directional component of the vector is mortified by using right-hand writing coordinate system. With combination of segment vectors which are adjacent and can be combined, the reconstruction of complete stroke is made out which is suitable for character recognition. As experimentation, it is verified that the proposed method is suitable for handwritten Korean character recognition.

• Nuclear Engineering and Technology
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• v.25 no.3
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• pp.424-429
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• 1993

Numeric characters are printed at the end part of nuclear fuel rod containing nuclear pellets. Fuel rods are discriminated and managed systematically by these characters in the process of producing fuel assembly. The characters are also used to examine manufacturing process of fuel rods in the survey of burnup efficiency as well as in inspection of irradiated fuel rod. Therefore automatic character recognition is one of the most important technologies in automatic manufacture of fuel assembly. In this study, character recognition system is developed. In the developed system, mesh feature extracted from each character written in the fuel rod has been compared with reference feature value stored in database, and the character is thus identified. In the result of experiment, 95.83 percent recognition rate is achievable.

• Proceedings of the Korean Information Science Society Conference
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• 2000.10b
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• pp.335-337
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• 2000

본 연구에서는 문자 인식의 응용으로서 인쇄된 우편봉투의 주소를 인식한다. 스캐너로 입력된 우편봉투 영상으로부터 주소영역과 우편번호 영역을 분리한다. 분리된 각각의 영역에서 문자를 추출하고, 전처리로써 정규화, 특징추출 단계를 거쳐 우편번호와 주소를 각각 인식하였다. 이때, 우편번호 인식에 의하여 알 수 있는 주소와 실제로 인식한 주소의 신뢰도를 계산하여, 주소 인식 결과를 보정하는 과정을 거쳐 우편봉투의 인식을 실행하였다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.5
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• pp.983-989
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• 2006

Current emigration and immigration control inspects passports by the naked eye, registers them by manual input, and compares them with items of database. In this paper, we propose the method to recognize information codes of passports. The proposed passport recognition method extracts character-rows of information codes by applying sobel operator, horizontal smearing, and contour tracking algorithm. The extracted letter-row regions is binarized. After a CDM mask is applied to them in order to recover the individual codes, the individual codes are extracted by applying vertical smearing. The recognizing of individual codes is performed by the RBF network whose hidden layer is applied by ART 2 algorithm and whose learning between the hidden layer and the output layer is applied by a generalized delta learning method. After a photo region is extracted from the reference of the starting point of the extracted character-rows of information codes, that region is verified by the information of luminance, edge, and hue. The verified photo region is certified by the classified features by the ART 2 algorithm. The comparing experiment with real passport images confirmed the good performance of the proposed method.

• Proceedings of the Korean Information Science Society Conference
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• 2000.10b
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• pp.407-409
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• 2000

본 논문에서는 Web 기반의 원격 교육 환경에서 강사와 학습자 모두에게 도움을 줄 수 있는 판서장면 MPEG Stream Data에서의 온라인 문자 인식 방법에 대하여 연구하였다. 강사가 별도의 프리젠테이션 자료를 만들 필요 없이 직접 판서한 MPEG Stream Data로부터 초당 3 Frame을 Sampling 한 후, 각 Frame에 Laplacian 마스크를 이용한 윤곽선 검출, Frame간 빼기 그리고 세선화 등의 영상처리 기법을 적용하여 문자인식에 필요한 좌표 값과 방향코드 등의 특징을 추출하였다. 좌표 값은 세선화 된 획의 중간 Pixel의 좌표 값이며, 구해진 좌표 값들을 이용하여 8방향 코드와 가상 획 코드를 구한 다음, 이 특징들을 사용해 은닉 마르코프 모델(Hidden Markov Model)을 학습시키고 한글 문자 인식을 행하였다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2011.10a
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• pp.907-910
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• 2011

This paper proposes a character segmentation algorithm of steel plate images composed of adaptive binarization by the SCW (Sliding Concentric Windows) technique, the object labelling by CCA (Connected Component Analysis), and 2D projection method. The SCW technique carries out the grayscale-to-binary image conversion in consideration of local characteristics of images. The character decision algorithm followed by the labelling technique by CCA (Connected Component Analysis) determines the character area effectively reducing the noise effect. The 2D projection with horizontal and vertical directions produces a tight bounding box for a character based on the cross points. Experimental results indicate that the proposed algorithm segments the characters in steel plate images effectively. The proposed algorithm can be applied to the devices with limited resources due to its excellent performance and low complexity.

• Journal of the Korea Society of Computer and Information
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• v.14 no.10
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• pp.73-82
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• 2009

This paper proposes a variance recovery method for character strokes that can be missed in applying the previously proposed color variance approach in text detection of natural scene images. The previous method has a shortcoming of missing the color variance due to the fixed length of horizontal and vertical windows of variance detection when the character strokes are thick or long. Thus, this paper proposes a variance recovery method by using geometric information of bounding boxes of connected components and heuristic knowledge. We have tested the proposed method using various kinds of document-style and natural scene images such as billboards, signboards, etc captured by digital cameras and mobile-phone cameras. And we showed the improved text detection accuracy even in the images of containing large characters.

• The Transactions of the Korea Information Processing Society
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• v.5 no.1
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• pp.223-235
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• 1998

도면 중에 내재한 지리정보를 이해해서 공간 자료에 대한 사용자의 질의에 응답할 수 있는 지능형 시스템의 설계는 화상처리 연구의 중요한 응용분야이다. 특히, 지도도면에는 도로, 강, 지역경계, 문자, 심벌 등의 지리정보가 존재하며, 이 개체와 개체 사이의 관계를 포함하는 데이터베이스의 구축은 매우 어려운 일이다. 본 논문에서는 지도도면으로부터 문자정보의 추출과 인식을 위해서 시신경계의 특징추출 이론을 적용한 공간 필터링 신경회로망을 제안한다. 본 시스템을 국립지리원 발행의 1/5,000지도에 적용하여 그 유효성을 보인다.