• The Transactions of the Korea Information Processing Society
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• v.6 no.12
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• pp.3683-3693
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• 1999

Most recognition methods of car licence plate have difficulties concerning plate recognition rates and system stability in that restricted car images are used and good image capture environment is required. To overcome these difficulties, I proposed a new recognition method of car licence plates, in which both intensity variation and color information are used. For a captured car image, multiple candidate plate-bands are extracted based on the number of intensity variation. To have an equal performance on abnormally dark and bright Images. plate lightness is calculated and adjusted based on the brightness of plate background. Candidate plate regions are extracted using contour following on plate color pixels in oath plate band. A candidate region is decided as a real plate region after extracting character regions and then recognizing them. I recognize characters using template matching since total number of possible characters is small and they art machine printed. To show the efficiency of the proposed method, I tested it on 200 car images and found that the method shows good performance.

• The Journal of Korean Academy of Prosthodontics
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• v.43 no.4
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• pp.466-477
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• 2005

Statement of problem : Problem of matching the appearance of porcelain restorations with the patient's natural dentition has always been a concern to dental clinicians. Recently, demands for esthetics, even in restorations requiring strength, has brought a revolution to dentistry and increased use of zirconia. Among the various factors, shade and translucency or the core can significantly affect the overall esthetics of the restoration and should be considered when selecting an all-ceramic system. Purpose : The purpose of this study was to spectrophotometrically evaluate the influence of different zirconia systems and core thickness on the final shade of all-ceramic restorations using the CIEL$^*a^*b^*$ system. Material and Methods: Core specimens (n : 20 per group) of In-Ceram Alumina, In-Ceram Zirconia, Digident CAD/CAM Zirconia, Cercon Zirconia were fabricated 20mm in diameter. 10 specimens of each group were fabricated at core thickness of 0.5mm and 0.7mm. These core specimens were veneered with shade Al & A3 porcelain of the recommended manufacturer. CIEL$^*a^*b^*$ coordinates were recorded for each specimen with a spectrophotometer (Model CM-2600d, Minolta, Japan). Color differences were calculated using the equation ${\Delta}E^*=[({\Delta}L^*)^2+({\Delta}a^*)^2+({\Delta}b^*)^2]^{\frac{1}{2}}$. Results : 1. Specimens of core thickness 0.5mm and 0.7mm did not exhibit clinically perceived color difference. 2. Regarding shade reproducibility, In-Ceram Alumina and In-Ceram Zirconia showed significant difference within each group. 3. Cercon Zirconia group showed the highest $L^*$ value and Digident Zirconia group showed lowest $a^*$ & $b^*$ value. 4. Generally the shade difference between materials was higher in the A3 shade group than in the Al shade group. Conclusion: Within the limitations of this study, there was no color difference after increase in core thickness and every all-ceramic system has color characteristics that clinicians have to consider when selecting materials. Also, manufacturers of different porcelain systems must make every effort to achieve color reproducibility.

• Journal of Broadcast Engineering
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• v.17 no.3
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• pp.437-446
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• 2012

A face detection algorithms using two-dimensional (2-D) intensity or color images have been studied for decades. Recently, with the development of low-cost range sensor, three-dimensional (3-D) information (i.e., depth image that represents the distance between a camera and objects) can be easily used to reliably extract facial features. Most people have a similar pattern of 3-D facial structure. This paper proposes a face detection method using intensity and depth images. At first, adaboost algorithm using intensity image classifies face and nonface candidate regions. Each candidate region is divided into $5{\times}5$ blocks and depth values are averaged in each block. Then, $5{\times}5$ block rank pattern is constructed by sorting block averages of depth values. Finally, candidate regions are classified as face and nonface regions by matching the constructed depth map based block rank patterns and a template pattern that is generated from training data set. For template matching, the $5{\times}5$ template block rank pattern is prior constructed by averaging block ranks using training data set. The proposed algorithm is tested on real images obtained by Kinect range sensor. Experimental results show that the proposed algorithm effectively eliminates most false positives with true positives well preserved.

• Proceedings of the Korean Society of Computer Information Conference
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• 2013.01a
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• pp.227-228
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• 2013

본 논문에서는 연속적으로 입력되는 스테레오 입체 영상으로부터 2차원과 3차원의 특징을 결합하여 군집화함으로써 대상 물체를 보다 강건하게 분할하는 기법을 제안한다. 제안된 방법에서는 촬영된 장면의 좌우 영상으로부터 스테레오 정합 알고리즘을 이용해 영상의 각 화소별로 카메라와 물체 사이의 거리를 나타내는 깊이 특징을 추출한다. 그런 다음, 깊이와 색상 특징을 효과적으로 군집화하여 배경에 해당하는 영역을 제외하고, 전경에 해당하는 대상 물체를 감지한다. 실험에서는 제안된 방법을 여러가지 영상에 적용하여 테스트를 해 보았으며, 제안된 방법이 기존의 2차원 기반의 물체 분리 방법에 비해 보다 강건하게 대상물체를 분할함을 확인하였다.

• Maxillofacial Plastic and Reconstructive Surgery
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• v.11 no.1
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• pp.283-286
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• 1989

The buccal mucosa is an effevtive and versatile intraoral grafting material. For adequate reconst ruction of avulsed lip, restoration of natural appearance and adequate lip function should be done. We treated avulsed upper lip defect which had been affected underlying orbicularis oris muscle as well as vermilion border. We chose cheek mucosa for upper lip reconstruction and performed surgical correction of avulsed upper lip with pedicled buccal mucosal flap. The result was very good because of its superior color and texture matching to remaining yermilion tissue.

• Proceedings of the Korean Information Science Society Conference
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• 2003.04c
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• pp.262-264
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• 2003

얼굴영상을 효율적으로 처리하기 위해선 먼저 입력영상에서 얼굴영역과 얼굴을 구성하는 각 기관을 검출하는 전처리과정이 필요하다. 본 논문에서는 얼굴의 크기와 얼굴의 회전, 조영의 변화가 어느 정도 허용되고 피부색 배경이 얼굴에 병합된 경우에도 얼굴영역과 얼굴기관(눈, 입)을 강건하게 검출할 수 있는 방법으로, 입력영상에 따른 적응적 칼라 색상정보와 얼굴기관의 부분 템플릿매칭을 조합한 알고리즘을 제안한다. 변환된 HSV 칼라 좌표계상의 대역적 피부색상 정보와 히스토그램을 이용한 적응적 피부색상 정보로 얼굴영역을 검출한 뒤, 얼굴영역 안에서 입술색상 정보로 도출된 입술영역의 X축 기울기를 이용해 회전얼굴을 보정하고, 양안의 조합으로 이루어진 부분 템플릿을 이용해 눈을 검출한다.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2004.10a
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• pp.454-457
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• 2004

AGV for FMS must be detected an obstacle. Therefore, many studies have been advanced, and recently, the ultra sonic sensor is used for this. However, the new method has to be developed because the ultra-sonic-sensor has many problems as a noise in factory, an directional error and detection of the obstacle size. So, we study the fast stereo vision system that can give more information to obstacles for intelligent AGV system. For this, the simulated AGV system was made with two CCD cameras in front to get the stereo images, and the threshold process by color information (intensity and chromaticity) and structure stereo matching method were constructed.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2001.12a
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• pp.299-302
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• 2001

The statistical analysis of the feature extraction and the neural networks are proposed to recognize a human face. In the preprocessing step, the normalized skin color map with Gaussian functions is employed to extract the region of face candidate. The feature information in the region of the face candidate is used to detect the face region. In the recognition step, as a tested, the 120 images of 10 persons are trained by the backpropagation algorithm. The images of each person are obtained from the various direction, pose, and facial expression. Input variables of the neural networks are the geometrical feature information and the feature information that comes from the eigenface spaces. The simulation results of$.$10 persons show that the proposed method yields high recognition rates.

• Journal of Biosystems Engineering
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• v.23 no.4
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• pp.373-380
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• 1998

The contribution of this paper is to provide the methods for the production automation of potato microtuber using the vision process in growth monitoring. The first method deals with computation for the growth density in the primary growth process. The second method addresses cognition process to identify the number and the volume of potato microtuber in secondary growth process. The third is to decide whether potato microtubers are infected by a virus or bacteria in growth process. The computation for the growth density in the primary growth process uses the method of Labeling. The second and third methods use template matching based on color patterns. With the developed method using vision process, this experiment is capable of discriminating weekly growth-rate in primary growth process, 85% cognition rate in secondary process and identifying whether there are infections. Therefore, we conclude that our experimental results are capable of growth monitoring for mass production of potato microtubers.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2013.06a
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• pp.45-46
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• 2013

본 논문에서는 깊이 영상과 컬러 영상의 매칭을 통한 강인한 전경 객체 영역화 기법을 제안한다. 기존의 컬러 영상 기반 객체 영역화 알고리즘은 배경과 객체의 색상이 유사한 경우 정확한 객체 영역화가 어렵다. 깊이 영상을 이용하면 이러한 오 검출을 줄일 수 있지만, 깊이 영상 취득 장비의 오류로 인하여 검출되는 객체 외곽선이 컬러 영상에 비해 세밀하지 못한 단점이 있다. 따라서, 깊이 영상의 외곽선을 비교적 세밀한 컬러 영상의 외곽선에 매칭시킨다. 아울러, 서로 다른 센서에서 취득한 두 영상을 매칭하기 위하여, 정규화된 상호연관성(normalized cross correlation)을 유사도 척도로 사용한다. 실험을 통하여 제안하는 알고리즘이 전경 객체 영역화의 오 검출을 줄이며, 동시에 객체 외곽선을 충실히 복원함을 확인한다.