• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.11
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• pp.2429-2434
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• 2010

In this paper, we propose a method to extract and analyze palm line with fuzzy method. In order to extract the palm part, we transform the original RGB color space to YCbCr color space and extract sin colors ranging Y:65-255, Cb:25-255, Cr:130-255 and use it as a threshold. Possible noise is removed by 8-directional contour tracking algorithm and morphological characteristic of the palm. Then the edge is extracted from that noise-free image by stretching method and sobel mask Then the fuzzy binarization algorithm is applied to remove any minute noise so that we have only the palm lines and the boundary of the hand. Since the palm line reading is done with major lines, we use the morphological characteristics of the analyzable palm lines and fuzzy inference rules. Experiment verifies that the proposed method is better in visibility and thus more analyzable in palm reading than the old method.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.8 no.1
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• pp.80-87
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• 2004

In this paper we proposed the novel feature extraction method that is able to extract the individual characters from the license plate area of the car image more precisely by using the RGB color information and the fuzzy binarization newly proposed. The proposed method, first, extracts from the original image the areas that the pixels with the colors around the green are concentrated on as the candidate areas of the license plate, and selects the area with the most intensive distribution of pixels with the white color among the candidate areas as the license plate area. Second the noises of the license plate area should be removed by using 34{\times}$3 Sobel masking, and the fuzzy binarization method are proposed and applied to the license plate area to generate the binarized image of the license plate area. Lastly, the application of the contour tracking algorithm to the binarized area extracts the individual characters from the license plate area. The experiment on a variety of the real car images showed that the proposed method generates the higher rate of success for character extraction than the previous methods.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.5
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• pp.1004-1012
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• 2007

In this paper, we proposed a new car license plate recognition method using an unsupervised ART2 algorithm with HSI color model. The proposed method consists of two main modules; extracting plate area from a vehicle image and recognizing the characters in the plate after that. To extract plate area, hue(H) component of HSI color model is used, and the sub-area containing characters is acquired using modified fuzzy binarization method. Each character is further divided by a 4-directional edge tracking algorithm. To recognize the separated characters, noise-robust ART2 algorithm is employed. When the proposed algorithm is applied to recognize license plate characters, the extraction rate is better than that of existing RGB model and the overall recognition rate is about 97.4%.

• KIPS Transactions on Software and Data Engineering
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• v.2 no.12
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• pp.889-898
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• 2013

Due to the popularization of high-performance capturing equipments and the emergence of powerful image-editing softwares, it is easy to make high-quality counterfeit money. However, the probability of detecting counterfeit money to the general public is extremely low and the detection device is expensive. In this paper, a counterfeit money detection algorithm using a general purpose scanner and computer system is proposed. First, the printing features of color printers are calculated using morphological operations and gray-level co-occurrence matrix. Then, these features are used to train a support vector machine classifier. This trained classifier is applied for identifying either original or counterfeit money. In the experiment, we measured the detection rate between the original and counterfeit money. Also, the printing source was identified. The proposed algorithm was compared with the algorithm using wiener filter to identify color printing source. The accuracy for identifying counterfeit money was 91.92%. The accuracy for identifying the printing source was over 94.5%. The results support that the proposed algorithm performs better than previous researches.

• The Journal of the Korea Contents Association
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• v.13 no.1
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• pp.9-18
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• 2013

In order to measure the parameters of consumers' preferred image quality, this research suggests image quality assessment factors; dynamic range, color, and contrast. They have both physical image quality factors and psychological characteristics from the previous researches. We found out the specific ranges of preferred image quality metrics. As a result, Digital Zone System meant for dynamic range generally shows 6~10 stop ranges in portrait, nightscape, and landscape. Total RGB mean values represent in portrait (67.2~215.2), nightscape (46~142), and landscape (52~185). Portrait total RGB averages have the widest range, landscape, and nightscape, respectively. Total scene contrast ranges show in portrait (196~589), nightscape (131~575), and landscape (104~767). Especially in portrait, skin tone RGB mean values are in ZONE V as the exposure standard, but practically image consumers' preferred skin tone level is in ZONE IV. Also, total scene versus main subject contrast ratio represents 1:1.2; therefore, we conclude that image consumers prefer the out-of-focus effect in portrait. Throughout this research, we can measure the preferred image quality metrics ranges. Also, we expect the practical and specific dynamic range, color, and contrast information of preferred image quality to positively influence product development.

• The Journal of the Korea Contents Association
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• v.19 no.10
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• pp.353-363
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• 2019

This study is for the use of color recommendation system for the color combination of mobile application. For this study, color combination methods of a material design color system that recommends harmonized colors automatically and of a mobile web application were applied to a mobile application design and a color combination experiment was carried out. Then for a survey on the experiment using the two methods, color combinations, selected colors and satisfaction with outputs were investigated on a 7-point Likert scale. And color combination characteristics of outputs were compared. It was found that the material design color palette made it easy to select colors by systematizing the regular coloring stages of fixed colors automatically, but there were differences in color compositions and color scopes of dominant color, assort color and accent colors, which are three-color combinations of mobile web application and accent color selection function was required for each design, since only primary colors and secondary colors could be selected. Moreover, chromatic colors were used a lot in the material system because of the fixed color scopes and color combination scopes and images of color combination outcomes varied depending on the color combination scopes, even when tones with a big contrast or complementary colors were selected. The role of color composition was important according to the color combination scopes.

• Proceedings of the Materials Research Society of Korea Conference
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• 2003.03a
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• pp.98-98
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• 2003

비정질 실리콘 박막을 태양전지, 박막 트랜지스터, 이미지 센서, 컬러 디텍터 등에 적용하기 위한 많은 연구가 진행되고 있다. 이중 태양전지에 적용하기 위한 비정질 실리콘 박막은 p/i/n 다이오드 구조를 형성하게 되는데, 태양전지의 효율을 증가시키기 위해 결정질을 형성하거나 실리콘 화합물 박막을 적용한다. 본 연구에서는 비정질 태양전지의 흡수층(absorption layer)으로 사용되는 수소화된 비정질 박막의 결정화에 수소의 희석비가 미치는 영향을 파악하고자 하였다. PECVD 장비로 실란(SiH$_4$)과 수소(H$_2$) 가스를 이용하여 실리콘 박막을 증착하였고, 수소의 희석비(dilution ratio)를 변화시켜 비정질 실리콘 박막 내에 결정질 실리콘이 형성되는 정도를 관찰하였다. SEM과 Raman Spectroscopy를 이용해 박막의 두께 및 결정화도를 측정하였다. 실란에 대한 수소의 희석비가 증가할수록 증착률은 낮아지지만, 결정화도가 높아지는 것을 관찰할 수 있었다. 본 연구에서 형성한 결정질 실리콘 박막을 태양전지의 흡수층에 적용하면 효율 증가에 크게 기여할 것으로 판단된다.

• Journal of the Korea Society of Computer and Information
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• v.13 no.6
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• pp.147-154
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• 2008

First, this paper compute difference value between frames using the composed method of $X^2$ histogram and color histogram and the normalization. Next, cluster representative frame was decided by using the clustering for distance and the k-mean grouping. Finally, representative frame of group was decided by using the likelihood ratio. Proposed method can be known by experiment as outstanding of detection rather than other methods, due to computing of difference value, clustering and grouping, and detecting of representative frame.

• Proceedings of the Korean Information Science Society Conference
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• 2003.10b
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• pp.715-717
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• 2003

2차원 의료 영상으로부터 3차원 모델을 재구성 하면 여러 의학 분야에 효과적으로 활용할 수 있다. 컬러 영상이나 MRI의 영상은 표면을 자동으로 식별하기 어렵기 때문에 구역화한 결과로 나오는 외곽선으로부터 표면을 재구성해야한다. 표면 재구성을 위한 기존의 삼각형화 알고리즘은 모델이 복잡할 경우 수행속도가 저하되는 단점이 있다. 본 논문에서는 정합되는 부분과 나머지 부분을 따로 처리하는 기존 방법 대신에, 알맞은 위치에 연결간선들만 결정하여 연결한 후, 그 사이의 정점들을 연결하는 간단한 삼각형화 알고리즘으로 속도를 향상시키는 방법을 제안한다.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2022.06a
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• pp.1286-1289
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• 2022

최근 영상 군집화 분야는 딥러닝 모델에게 Self-supervision을 주거나 unlabeled 영상에 유사-레이블을 주는 방식으로 연구되고 있다. 또한, 고차원 컬러 자연 영상에 대해 잘 압축된 특징 벡터를 추출하는 것은 군집화에 있어 중요한 기준이 된다. 본 연구에서는 자연 영상에 대한 Convolutional Auto Encoder의 특징 추출 성능을 평가하기 위해 설계한 실험 방법을 소개한다. 특히 모델의 특징 추출 능력을 순수하게 확인하기 위하여 Self-supervision 및 유사-레이블을 제공하지 않은 채 Naive한 모델의 결과를 분석할 것이다. 먼저 실험을 위해 설계된 4가지 비지도학습 모델의 복원 결과를 통해 모델별 학습 정도를 확인한다. 그리고 비지도 모델이 다량의 unlabeled 영상으로 학습되어도 더 적은 labeled 데이터로 학습된 지도학습 모델의 특징 추출 성능에 못 미침을 특징 벡터의 군집화 및 분류 실험 결과를 통해 확인한다. 또한, 지도학습 모델에 데이터셋 간 교차 학습을 수행하여 출력된 특징 벡터의 군집화 및 분류 성능도 확인한다.