• Journal of KIISE:Software and Applications
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• v.34 no.9
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• pp.797-803
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• 2007

Adaptive binarization is very important for the camera-based document recognition. This paper proposes a binarization method which can effectively adapt to the variation of image Qualify. Firstly, it analyzes the effect of binarization parameters to the result and proposes a method to measure the image quality. Then, it statistically analyzes the relationship between the image quality and the binarization parameter. Finally, it proposes a binarization method that automatically adapts to the quality of the input image, using the analysis result. The experiment results show that there is a meaningful relationship between the image quality and the binarization parameter, and therefore, the proposed method can effectively adapt to the variation of image quality.

• Journal of the Korean Institute of Intelligent Systems
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• v.12 no.3
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• pp.227-230
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• 2002

An important preprocessing for fingerprint recognition is the binarization operation, which takes as an input gray-scale image and returns a binary image as the output. The difficult in performing binarization is to find an appropriate threshold value. This paper presents a new adaptive binarization method, which determines the threshold value according to the brightness of local ridges and valleys. We experimentally show that the presented method results in better performance than a traditional method.

• Proceedings of the Korea Information Processing Society Conference
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• 2006.11a
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• pp.65-68
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• 2006

카메라로 촬영한 문서 영상의 분석 및 인식을 위한 적응적 이진화 방법을 제안한다. 먼저 카메라 영상의 화질을 분석하여 정량화하는 방법을 제안한다. 그 후 다양한 화질의 카메라 영상에 대하여 제안한 방법으로 측정한 화질과 그 화질에 적합한 이진화 파라미터간의 상관 관계를 통계적으로 분석한다. 그 후 그들간의 상관 관계를 이용하여 입력 영상의 화질에 적합한 이진화 파라미터를 자동으로 추정하도록 함으로써 화질 변화에 대한 적응력을 강화하였다. 실험을 통해 초점 및 잡영의 상태에 따라 적절한 파라미터를 추정함으로써 화질 변화에 적응하는 결과를 확인하였다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2012.10a
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• pp.109-110
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• 2012

In this paper, we propose an adaptive thresholding method to binarize two-dimensional barcode images. Adaptive thresholding methods are applied to document image binarization. Thus, they inappropriate to use in recognition of two-dimensional barcode images. To overcome the problem, we propose a new adaptive threshold method using the integral image. To show the effectiveness of our method, we compared our method with the well-known existing method in terms of visual quality and processing time. The experimental result indicates that the proposed method is superior to the existing method.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.11
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• pp.2453-2458
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• 2012

In this paper, we propose an adaptive thresholding method to binarize two-dimensional barcode images. Adaptive thresholding methods that minimize light effects convert an original image into a binary image. The methods are applied to document image binarization. The methods, however, have problems of determining box size used in adaptive thresholding. thus, they inappropriate to use in recognition of two-dimensional barcode images. To overcome the problem, we analysis the problem and propose a new adaptive threshold method using the integral image. To show the effectiveness of our method, we compared our method with the well-known existing methods in terms of visual quality and processing time. The experimental result indicates that the proposed method is superior to the existing method.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.10a
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• pp.517-519
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• 2016

본 논문에서는 적응적 이진화 기법을 적용하여 흠집 영역을 검출한다. 제안된 방법은 안경 렌즈 영상에서 명암 대비를 적용하여 렌즈의 명암을 강조한다. 명암이 강조된 영상에서 렌즈 밖의 배경 영역은 흠집 검출에 불필요하므로 개선된 평균 이진화 기법을 적용한 후에 렌즈의 윤곽선을 검출하여 렌즈 이외의 배경을 제거한다. 렌즈 이외의 배경이 제거된 렌즈 영상에서 렌즈 내부에 명암대비를 적용하여 렌즈 내부의 배경과 흠집의 명암을 강조한다. 명암이 강조된 렌즈 내부 영역에서 적응적 이진화 기법을 적용하여 흠집과 잡음을 검출한다. 잡음은 중간값 필터를 적용하여 제거한 후에 흠집 영역을 추출한다. 추출된 흠집 영역을 렌즈의 중심으로부터의 거리와 흠집의 크기를 퍼지 추론 규칙을 적용하여 눈에 미치는 영향 정도를 분석한다. 본 논문에서 제안된 방법의 성능을 분석하기 위해 CHEMI, MID, HL, HM과 같은 시력 보정용 렌즈 영상 6장을 대상으로 실험한 결과, 제안된 방법이 기존 렌즈 흠집 추출 방법보다 흠집 영역이 정확하게 추출되었고 눈에 미치는 영향을 효과적으로 분석할 수 있는 가능성을 확인하였다.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.6C
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• pp.801-814
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• 2004

In this paper, we propose a block adaptive binarization (BAB) using a modified quadratic filter (MQF) to binarize business card images acquired by personal digital assistant (PDA) cameras effectively. In the proposed method, a business card image is first partitioned into blocks of 8${\times}$8 and the blocks are then classified into character Hocks (CBs) and background blocks (BBs). Each classified CB is windowed with a 24${\times}$24 rectangular window centering around the CB and the windowed blocks are improved by the pre-processing filter MQF, in which the scheme of threshold selection in QF is modified. The 8${\times}$8 center block of the improved block is barbarized with the threshold selected in the MQF. A binary image is obtained tiling each binarized block in its original position. Experimental results show that the MQF and the BAB have much better effects on the performance of binarization compared to the QF and the global binarization (GB), respectively, for the test business card images acquired in a PDA. Also the proposed BAB using MQF gives binary images of much better quality, in which the characters appear much better clearly, over the conventional GB using QF. In addition, the binary images by the proposed BAB using MQF yields about 87.7% of character recognition rate so that about 32.0% performance improvement over those by the GB using QF yielding about 55.7% of character recognition rate using a commercial character recognition software.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09b
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• pp.155-161
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• 2003

출입국 관리 절차를 간소화하는 방안의 하나로 퍼지 신경망을 이용한 여권 인식 시스템을 제안한다. 제안된 여권 인식 방법은 소벨 연산자와 수평 스미어링, 윤곽선 추적 알고리즘을 적용하여 코드의 문자열 영역을 추출한다 여권의 문자열 영역은 OCR 문자 서체로 구성되어 있고, 명도 차이가 다양하게 나타난다. 따라서 추출된 문자열 영역을 블록 이진화와 평균 이진화를 각각 수행하고 그 결과들을 AND 비트 연산을 취하여 적응적으로 이진화한다. 이진화된 문자열 영역에 대해서 개별 코드의 문자들을 복원하기 위하여 CDM(Conditional Dilation Morphology) 마스크를 적용한 후, 역 CDM마스크와 HEM(Hit Erosion Morphology)마스크를 적용하여 잡음을 제거한다 잡음이 제거된 문자열 영역에 대해 수직 스미어링을 적용하여 개별 코드의 문자를 추출한다. 추출된 개별 코드의 인식은 퍼지 ART 알고리즘을 개선하여 RBF 네트워크의 중간층으로 적용하는 퍼지 RBF 네트워크와 개선된 퍼지 ART 알고리즘과 지도 학습을 결합한 퍼지 자가 생성 지도 학습 알고리 즘을 각각 제안하여 여권의 개별 코드 인식에 적용한다. 제안된 방법의 성능을 확인하기 위해서 실제 여권 영상을 대상으로 실험한 결과, 제안된 추출 및 인식 방법이 여권 인식에서 우수한 성능이 있음을 확인하였다.

• Journal of the Korean Institute of Intelligent Systems
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• v.26 no.6
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• pp.485-492
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• 2016

A role of the binarization is very important in separating the foreground and the background in the field of the computer vision. In this study, an adaptive fuzzy binarization is proposed. An ${\alpha}$-cut control ratio is obtained by the distribution of grey level of pixels in a sliding window, and binarization is performed using the value. To obtain the ${\alpha}$-cut, existing thresholding methods which execution speed is fast are used. The threshold values are set as the center of each membership function and the fuzzy intervals of the functions are specified with the distribution of grey level of the pixel. Then ${\alpha}$-control ratio is calculated using the specified function and binarization is performed according to the membership degree of the pixels. The experimental results show the proposed method can segment the foreground and the background well than existing binarization methods and decrease loss of the foreground.

• Journal of Korea Society of Industrial Information Systems
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• v.12 no.3
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• pp.132-140
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• 2007

The quality of the camera image is worse than that of the scanner image because of lighting variation and inaccurate focus. This paper proposes a binarization method for camera-based document recognition, which is tolerant to low-quality camera images. Based on an existing method reported to be effective in previous evaluations, we enhanced the adaptability to the image with a low contrast due to low intensity and inaccurate focus. Furthermore, applying an additional small-size window in the binarization process, it is effective to extract the fine detail of character structure, which is often degraded by conventional methods. In experiments, we applied the proposed method as well as other methods to a document recognizer and compared the performance for many cm images. The result showed the proposed method is effective for recognition of document images captured by the camera.