• Journal of the Korea Society of Computer and Information
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• v.15 no.10
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• pp.49-57
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• 2010

In this thesis, We studied on hand-written character recognition, that characters entered into a digital input device and remove noise and separating character elements using preprocessing. And processed character images has done thinning and 3-level wavelet transform for making normalized image and reducing image data. The structural method among the numerical Hangul recognition methods are suitable for recognition of printed or hand-written characters because it is usefull method deal with distortion. so that method are applied to separating elements and analysing texture. The results show that recognition by analysing texture is easily distinguished with respect to consonants. But hand-written characters are tend to decreasing successful recognition rate for the difficulty of extraction process of the starting point, of interconnection of each elements, of mis-recognition from vanishing at the thinning process, and complexity of character combinations. Some characters associated with the separation process is more complicated and sometime impossible to separating elements. However, analysis texture of the proposed character recognition with the exception of the complex handwritten is aware of the character.

• The Journal of the Korea Contents Association
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• v.8 no.11
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• pp.85-93
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• 2008

For music score recognition, several approaches have been proposed including shape matching, statistical methods, neural network based methods and structural methods. In this paper, we deal with recognition for low resolution images which are captured by the digital camera of a mobile phone. Considerable distortions are included in these low resolution images, so when existing technology is used, many problems appear. First, captured images are not stable in the sense that they contain lots of distortions or non-uniform illumination changes. Therefore, notes or symbols in the music score are damaged and recognition process gets difficult. This paper presents recognition technology to overcome these problems. First, musical note to head, stick, tail part are separated. Then template matching on head part of musical note, and remainder part is applied. Experimental results show nearly 100% recognition rate for music scores with single musical notes.

• Journal of Digital Contents Society
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• v.10 no.3
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• pp.413-421
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• 2009

Recently, various kinds of arcade games are offered through the network with the internet's development. And for the Grid Logic game, it is opened up for everyone who uses the internet but it has a disadvantage that only the provided puzzles can be played. To improve this, in this paper, we developed a Grid Logic game contents using an image of user's as a puzzle. In order to do this, we suggested a threshold decision method, the pre-processing stage of image processing. We showed a method of detecting aim image from a binary image, showed up by the suggested way, and a method of changing into the game data and carrier of the meaning as a specific image at the end of the game are the objects of this paper. The suggested algorithm is constructed as a Java applet and applied to the 10 objects such as characters, logos, persons, etc. to show that this algorithm is suitable for the appropriate acquisition of the Grid Logic game data through the experiment.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.2
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• pp.318-328
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• 2014

In this paper, as a way of performance improvement of business card recognition in the mobile environment, we suggested a hybrid OCR agent which combines data using a parallel processing sequence between various algorithms and different kinds of business card recognition engines which have learning data. We also suggested an Image Processing Method on mobile cameras which adapts to the changes of the lighting, exposing axis and the backgrounds of the cards which occur depending on the photographic conditions. In case a hybrid OCR agent is composed by the method suggested above, the average recognition rate of Korean business cards has improved from 90.69% to 95.5% compared to the cases where a single engine is used. By using the Image Processing Method, the image capacity has decreased to the average of 50%, and the recognition has improved from 83% to 92.48% showing 9.4% improvement.

• Journal of Korea Society of Industrial Information Systems
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• v.23 no.6
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• pp.21-27
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• 2018

Wearing degree and uneven wearing detection algorithm using horizontal edge information is proposed in this paper. The noise in the input image is removed by bilateral filter, and then edges are extracted from the filtered image by using the proposed mask. As the tire is worn, grooves of tire shoulder or sipes are changed more than the vertical grooves. Therefore the edges from grooves of tire shoulder or sipes have more information about the tire wearing than the edges from vertical grooves. Proposed mask that is reflected this feature is used to extract the horizontal edges. After edge extraction, the edge image is represented in two-level system. The edge pixels of the binarization image are used to decide the wearing degree and uneven wearing. This proposed method can be used easily without any other equipments. The proposed method is conducted with a real vehicle, and the experimental results show the good performance of the proposed method in detecting wearing degree and uneven wearing.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.463-465
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• 2021

Currently, the inspection method printed on food packages and boxes is to sample only a few products and inspect them with human eyes. Such a sampling inspection has the limitation that only a small number of products can be inspected. Therefore, accurate inspection using a camera is required. This paper proposes a deep learning object recognition technology model, which is an artificial intelligence technology, as a method for detecting the defects of expiration date printed on the product packaging. Using the Faster R-CNN (region convolution neural network) model, the color images, converted gray images, and converted binary images of the printed expiration date are trained and then tested, and each detection rates are compared. The detection performance of expiration date printed on the package by the proposed method showed the same detection performance as that of conventional vision-based inspection system.

• Proceedings of the Korean Information Science Society Conference
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• 2006.06a
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• pp.190-192
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• 2006

본 논문은 유리의 결함 검사를 위한 알고리즘을 제안한다. 기포 측정에 대한 정의와 기포의 형상을 측정하는 알고리즘을 제시하고, 비젼 시스템을 이용한 검사자동화 시스템에 적용하여 테스트를 하였다. 기포 형상에는 두가지 타입으로 원형 타입과 긴형상 타입으로 구분되며, 이 두가지 타입에 따라 측정 결과 표시 방법이 다르다. 이미지 획득 및 전저리에서는 ccd 카메라를 사용하여 획득한 영상과 결함을 찾기 위해 영상을 이진화를 했으며, 얻어진 이진영상은 chain code 알고리즘을 통해 결함의 면적, 둘레 길이 및 위치등의 정보를 추출한다. 실제 물리적 크기를 정확히 얻기 위해 카메라의 보정을 했다. 광학계의 심도에 비하여 패널의 두께가 두껍기 때문에 하나의 영상으로는 기포의 양질의 영상획득이 불가능하다. 이러한 문제를 해결하기 위하여 높이를 변화시켜가며 획득한 영상으로 불량형상을 찾아내고, 측정하기 적합한 영상을 획득하는 화상처리 알고리즘도 제안한다. 조명은 기존에 사용한 백라이트 명시야 조명을 사용하였다. 시스템의 결함 검출율은 거의 90%이상의 성능을 나타내고 있다.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.7 no.1
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• pp.32-41
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• 2008

The moving object tracking in vision based observation using video uses difference method between GMM(Gaussian Mixture Model) based background and present image. In the case of racking object using binary image made by threshold, the object is merged not by object information but by Cast-Shadow. This paper proposed the method that eliminates Cast-Shadow using backpropagation Neural Network. The neural network is trained by abstracting feature value form training image of object range in 10-movies and Cast-Shadow range. The method eliminating Cast-Shadow is based on the method distinguishing shadow from binary image, its Performance is better(16.2%, 38.2%, 28.1%, 22.3%, 44.4%) than existing Cast-Shadow elimination algorithm(SNP, SP, DNM1, DNM2, CNCC).

• Proceedings of the Korea Information Processing Society Conference
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• 2018.05a
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• pp.481-483
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• 2018

AR은 VR과 달리 실세계 공간의 객체에 대한 서비스를 제공하므로 서비스 개발을 방해하는 많은 요인들이 발생한다. 이를 보완하기위해 비주얼 마커, SLAM, 객체인식 등 여러 AR 기술이 존재한다. 본 논문은 AR 기술 중에서 객체인식의 정확도 향상을 위해 지역가변 이진화(Local variable binarization)와 색상의 군집화를 사용해서 이미지에서 객체를 추출하는 방법을 제안한다. 지역 가변화는 픽셀을 순차적으로 읽어 들이면서 픽셀 주위의 값의 평균을 구하고, 이 값을 해당 픽셀의 임계 값으로 사용하는 알고리즘이다. 픽셀마다 주위 색상 값에 의해 임계 값이 변화되므로 윤곽선 표현이 기존의 이진화보다 뚜렷이 나타난다. 색상의 군집화는 객체의 중요색상과 배경의 중요색상을 중심으로 유사한 색상끼리 군집화 하는 것이다. 객체 내에서 가장 많이 나온 값과 객체 외에 가장 많이 나온 값을 각 각 기준으로 색조와 채도의 값을 Euclidean 거리를 사용해 객체의 색상과 배경 색상을 분리했다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.10
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• pp.1787-1793
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• 2008

Fingerprint Recognition System is made up of Off-line treatment and On-line treatment; the one is registering all the information of there trieving features which are retrieved in the digitalized fingerprint getting out of the analog fingerprint through the fingerprint acquisition device and the other is the treatment making the decision whether the users are approved to be accessed to the system or not with matching them with the fingerprint features which are retrieved and database from the input fingerprint when the users are approaching the system to use. In this paper, we propose a new data structure, called Union and Division, for processing binarized digital fingerprint image efficiently. We present a minutiae extraction algorithm that is using Union and Division and consists of binarization, noise removal, minutiae extraction stages.