• Korean Journal of Optics and Photonics
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• v.19 no.3
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• pp.161-168
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• 2008

We propose a novel bistable nematic liquid crystal cell, which has a dual-frequency liquid crystal material and pixel-isolating polymer wall formed by an anisotropic phase separation of a mixture of liquid crystals and UV-curable pre-polymers. The proposed cell has two stable states of left- and right-handed ${\pi}$-twist. The switching between the two states is achieved by using a sequential waveform of low and high frequencies. A transmissive bistable liquid crystal display is designed, which achieves high contrast ratio by using the proposed cell and optical films.

• Proceedings of the Optical Society of Korea Conference
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• 2005.07a
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• pp.140-141
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• 2005

• Korean Journal of Remote Sensing
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• v.33 no.5_2
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• pp.689-698
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• 2017

In this paper, a new classification method based on the combination of semi-supervised learning with spatial similarity of adjacent pixels is presented for crop classification in inaccessible areas. Iterative classification based on semi-supervised learning is applied to extract reliable training data from both the initial classification result with a small number of training data, and classification results of adjacent pixels are also considered to extract new training pixels with less uncertainty. To evaluate the applicability of the proposed method, a case study of the classification of field crops was carried out using multi-temporal Landsat-8 OLI acquired in the Daehongdan region, North Korea. From a case study, the misclassification of crops and forests, and isolated pixels in the initial classification result were greatly reduced by applying the proposed semi-supervised learning method. In addition, the combination of classification results of adjacent pixels for the extraction of new training data led to the great reduction of both misclassification results and isolated pixels, compared to the initial classification and traditional semi-supervised learning results. Therefore, it is expected that the proposed method would be effectively applied to classify areas in which it is difficult to collect sufficient training data.

• Proceedings of the Korea Institute of Convergence Signal Processing
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• 2000.12a
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• pp.97-100
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• 2000

본 논문에서는 얼굴의 특징 추출 알고리즘을 제안한다. 입력 영상을 이진 영상으로 처리한 후, 얼굴 요소 후보 블록의 면적, 둘레, 원형도, 종횡비를 이용하여 불변하는 눈, 코, 입의 특징 요소를 추출한다. 사람의 얼굴에 대한 특징 요소를 추출하기 위하여 우선 이진 영상을 생성한다. 하나 하나의 고립된 영역으로 분리하기 위하여 화소 레이블링을 한 후 만들어진 얼굴 요소 후보 블록 단위로 면적을 구하고, 윤곽선 추적 방법에 의하여 둘레를 구한 다음 면적, 둘레, 원형도 및 종횡비의 유사도를 구한다 블록의 종합 유사도, 대칭적 거리, 위치의 유사도를 활용하여 눈, 코, 입을 추출한다. 추출된 각 특징 요소간의 거리와 각도를 이용하여 12개의 특징 인수를 구하는 제안 알고리즘을 수행함으로써 얼굴의 특징 인수들을 추출한다. 각 특징점 사이의 거리와 각 거리간의 기울기를 이용하여 100명으로부터 획득한 297개의 원 영상을 대상으로 12개의 특징 파라미터를 추출한 결과 92.93%의 추출 성공률을 보였다. 이러한 결과는 외부 환경의 영향을 덜 받는 눈, 코, 입의 위치 관계의 블록을 근거로 특징 요소를 추출할 수 있도록 제안 알고리즘을 구성하였던 것으로 판단된다.

• The Journal of the Korea Contents Association
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• v.9 no.8
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• pp.91-98
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• 2009

This paper presents a solution to error avalanche of deciphering where radio noise brings random bit errors in encrypted image data under ubiquitous environment. The image capturing module is to be made comprising data compression and encryption features to reduce data traffic volume and to protect privacy. Block cipher algorithms may experience error avalanche: multiple pixel defects due to single bit error in an encrypted message. The new fault tolerant scheme addresses error avalanche effect exploiting a three-dimensional data shuffling process, which disperses error bits on many frames resulting in sparsely isolated errors. Averaging or majority voting with neighboring pixels can tolerate prominent pixel defects without increase in data volume due to error correction. This scheme has 33% lower data traffic load with respect to the conventional Hamming code based approach.

• Journal of the Institute of Convergence Signal Processing
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• v.2 no.2
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• pp.47-54
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• 2001

The main purpose of this study is to propose the algorithm about the extraction of the facial feature. To achieve the above goal, first of all, this study produces binary image for input color image. It calculates area after pixel labeling by variant block-units. Secondly, by contour following, circumference have been calculated. So the proper degree of resemblance about area, circumference, the proper degree of a circle and shape have been calculated using the value of area and circumference. And Third, the algorithm about the methods of extracting parameters which are about the feature of eyes, nose, and mouse using the proper degree of resemblance, general structures and characteristics(symmetrical distance) in face have been accomplished. And then the feature parameters of the front face have been extracted. In this study, twelve facial feature parameters have been extracted by 297 test images taken from 100 people, and 92.93 % of the extracting rate has been shown.

• Korean Journal of Remote Sensing
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• v.38 no.5_1
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• pp.461-469
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• 2022

This paper presents a novel training data extraction approach using semi-supervised learning (SSL)-based classification without the analyst intervention for time-series land-cover mapping. The SSL-based approach first performs initial classification using initial training data obtained from past images including land-cover characteristics similar to the image to be classified. Reliable training data from the initial classification result are then extracted from SSL-based iterative classification using classification uncertainty information and class labels of neighboring pixels as constraints. The potential of the SSL-based training data extraction approach was evaluated from a classification experiment using unmanned aerial vehicle images in croplands. The use of new training data automatically extracted by the proposed SSL approach could significantly alleviate the misclassification in the initial classification result. In particular, isolated pixels were substantially reduced by considering spatial contextual information from adjacent pixels. Consequently, the classification accuracy of the proposed approach was similar to that of classification using manually extracted training data. These results indicate that the SSL-based iterative classification presented in this study could be effectively applied to automatically extract reliable training data for time-series land-cover mapping.

• Proceedings of the Korean Vacuum Society Conference
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• 2014.02a
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• pp.141.2-141.2
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• 2014

크라이오 펌프는 반도체 임플란타 공정, OLED 분야, 신소재 개발, 표면분석 및 처리, 의료분야, 입자가속기, 핵융합 등 다양한 진공분야에 응용되는 고진공용 극저온펌프이다. 특히 향후 디스플레이 분야에서 OLED가 시장을 주도할 것으로 예상되는 가운데, 점점 대형화 되어가는 OLED 장비에 가장 적합한 고진공 펌프로써 크라이오 펌프가 주목을 받고 있다. OLED 디스플레이 제조공정 중에서도 화소형성 공정을 위한 챔버는 특별히 진동특성에 민감하다. 유기물 증착공정을 진행하기 위해서 글라스 전단에 쉐도우 마스크를 설치하는데, 글라스의 크기가 증가하면서 초래된 처짐문제 그리고 장비의 진동특성과 글라스와 마스크 사이의 간섭문제 등이 제품의 수율에 큰 영향을 미치면서 향수 시급히 해결해야 할 필수 과제로 주목 받고 있다. 그러나 대부분의 상용 크리이오 펌프는 G-M형식의 냉동기를 장착하기 때문에 그 원리 상 제조사에 관계없이 일반적으로 큰 진동특성을 가진다. 이에 GVT에서는 OLED 공정에 적합한 보다 정숙하고 진동특성이 개선된 550 mm구경의 크라이오 펌프 개발을 진행하였다. 그 결과 펌프의 성능은 동종 경쟁모델과 동등 이상의 수준을 유지하고 진동성분은 동종모델 대비 50%이상 개선된 펌프를 개발할 수 있었다. 그리고 시장에 보다 좋은 제품을 출시하기 위해서 현재 성능과 진동특성을 계속해서 튜닝 중에 있다. 진동개선은 크게 2가지 방향으로 진행되었는데, 첫째는 펌프 측면에서 진행한 것이고 둘째는 냉동기 측면에서 진행한 것이다. 후자는 현재 대외비로 개발을 진행 중에 있으며 본 발표에서는 전자에 관한 것으로 펌프 측면에서 진동특성을 개선한 부분이다. 결국 크라이오 펌프의 진동은 진동원인 냉동기에서 발생하는 것이므로 냉동기와 펌프를 구조적으로 고립시키는 방법을 사용하였다. 즉, 냉동기와 펌프 사이에 댐핑 시스템 플랜지를 장착하여 진동원인 냉동기로부터 진동성분이 펌프 측으로 전달되는 것을 차단한 것이 본 기술의 핵심이다. GVT에서는 당 기술로 국내특허등록을 완료하였다(특허-10-1289394_진동 저감을 위한 댐핑 플랜지 조립체 및 이를 갖는 크라이오 펌프).

• Journal of Korea Society of Industrial Information Systems
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• v.12 no.3
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• pp.116-123
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• 2007

Despite the number of backlight manufacturer is increased as the market of flat panel display equipments and related development devices is enlarged, the inspection based on the human eye is still used in many backlight production lines. The defects such as particle, spot and scratch on the light emitting surface of the backlight prevent the LCD device from displaying the colors correctly. From that manual inspection it is difficult to maintain the quality of backlight consistently because the accuracy and the speed of the inspection may change with the physical condition of the operater. In this paper we studied on the development of automatic backlight surface defect inspection system. For this, we made up of the computer vision system and we developed the main program with various user interfaces to operate the inspection system effectively. And we developed the image processing module to extract the defect information. Furthermore, we presented the labeling process to reconstruct defect regions using the labeling table and the defect index. From the experimental results, we found that our system can detect all defect regions identified from human eye and it is sufficient to substitute for the conventional surface inspection.