• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.10
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• pp.1828-1834
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• 2007

This study proposes a new digital watermarking technique based on wavelet transformation on color image. First the $YC_bC_r$ coordinates obtain from RGB color space. then, the correlation of watermark is decreased by Arnold transformation. Next, watermark which has been enlarged by Linear Bit-expansion is inserted at a given intensity in Color images' low frequency sub-bands. When detecting the presence of watermark, F-norm function is applied. As a result of the various experiments on color images, the proposed watermarking technique has outstanding quality in regards to fidelity and robustness.

• Fashion Information and Technology
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• v.2
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• pp.3-13
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• 2005

• Proceedings of the Korean Information Science Society Conference
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• 2000.04b
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• pp.586-588
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• 2000

KUeyes는 3차원 실세계의 영상처리를 위해 고려대학교 인공시각연구센터에서 개발된 컬러 스테레오 헤드아이 시스템이다. KUeyes는 인간의 시각 시스템을 모델로 하여 다해상도 변환 영상, 칼라 정보와 거리 정보, 움직임 정보를 이용하여 지능적이고 빠르게 객체를 탐지하여 추적한다. 또한 병렬적으로 수행되는 인식기를 통해 탐지된 사람의 얼굴을 인식한다. 다양한 실험 및 분석을 통해 KUeyes가 복잡한 실영상을 대상으로 움직이는 개체를 신시간으로 안정되게 추적하고 인식하는 것을 확인할 수 있었다.

• Proceedings of the Korean Information Science Society Conference
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• 2001.10b
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• pp.433-435
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• 2001

얼굴 인식분야에서 실시간 얼굴검출에 대한 관심이 높아짐에 따라 피부색컬러 모델을 통한 얼굴영역검출에 대한 연구가 활발히 진행되고 있다. 그러나, 기존의 피부색 모델은 밝기 정보를 제거한 단일 채널의 색상모델이 대부분이다. 이에 본 논문에서는 얼굴피부색을 보다 효과적으로 모델링하기 위하여, 피부색 특성을 고려하여, 밝기 성분을 제거한 RGB 컬러를 모두 사용하는 H, Cb, Cg의 다채널 피부색 모델을 제시한다. 또한, 색상정보에서 사용하지 않은 밝기 정보는 영상 분할을 통해 사용한다. 제안하는 피부색 모델을 통한 얼굴영역 추출 과정을 보인다.

• Journal of Advanced Navigation Technology
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• v.15 no.3
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• pp.471-477
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• 2011

A wide distribution of CCTV cameras in many public areas can be used not only for video surveillance systems but also for preserving fire occurrence. A proposed approach is based on visual information through a static camera. Video sequences are analyzed to find fire candidates and then spatial analyses procedure for detected fire-like color foreground is carried out. If spatial and temporal variances changes rapidly and close to fire motion, fire candidate is considered as fire.

• Journal of the Korean Institute of Intelligent Systems
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• v.23 no.1
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• pp.57-64
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• 2013

In this paper, we propose the classification method of medicine bottle images using the features with color and size information. It is difficult to classify with size feature only, because there are many similar sizes of bottles. Therefore, we suggest a classification method based on color information, which robust to illumination variations. First, we extract MBR(Minimum Boundary Rectangle) of medicine bottle area using Binary Threshold of Red, Green, and Blue in image and classify images with size. Then, hue information and RGB color average rate are used to classify image, which features are robust to lighting variations. Finally, using SURF(Speed Up Robust Features) algorithm, corresponding image can be found from candidates with previous extracted features. The proposed method makes to reduce execution time and minimize the error rate and is confirmed to be reliable and efficient from experiment.

• The KIPS Transactions:PartD
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• v.13D no.1 s.104
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• pp.125-132
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• 2006

The existing recognition system of license plates cannot get the satisfactory result in noise environments. The purpose of this paper is to propose an algorithm that can recognize the region of license plates accurately in a noise environment. The algorithm is formulated by reorganizing the U- and V-channels of YUV color space as YUV is insensitive to light and carries less data than RGB color information. The region of license plates has been extracted by the geometric characteristics, sizes, and places of labeling images. The proposed algorithm was found to improve the process of extracting the region of license plates in various noise environments.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.45 no.6
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• pp.154-161
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• 2008

In this paper, a novel method is proposed using color and pattern information for recognizing some emotions included in a fertile. Here we use 10 Kobayashi emotion to represent emotions. - { romantic, clear, natural, casual, elegant chic, dynamic, classic, dandy, modem } The proposed system is composed of feature extraction and classification. To transform the subjective emotions as physical visual features, we extract representative colors and Patterns from textile. Here, the representative color prototypes are extracted by color quantization method, and patterns exacted by wavelet transform followed by statistical analysis. These exacted features are given as input to the neural network (NN)-based classifiers, which decides whether or not a textile had the corresponding emotion. When assessing the effectiveness of the proposed system with 389 textiles collected from various application domains such as interior, fashion, and artificial ones. The results showed that the proposed method has the precision of 100% and the recall of 99%, thereby it can be used in various textile industries.

• Journal of the Korea Society of Computer and Information
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• v.14 no.1
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• pp.135-143
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• 2009

Recently, in the mobile device, the increase of the need for encoding and decoding of high-resolution images requires an efficient implementation of the image codec. This paper proposes a time-optimized color conversion method for the JPEG decoder, which reduces the number of calculations in the color conversion by the rearrangement of arithmetic operations being possible due to the linearity of the IDCT and the color conversion matrices and brings down the time complexity of the color conversion itself by the integer mapping replacing floating-point operations to the optimal fixed-point shift and addition operations, eventually reducing the time complexity of the JPEG decoder. And the proposed method compensates a decline of image quality incurred by the quantification error of the operation arrangement and the integer mapping by using the multi-mode chrominance reconstruction. The performance evaluation performed on the development platform of embedded systems showed that, compared to previous color conversion methods, the proposed method greatly reduces the image decoding time, minimizing the distortion of decoded images.

• Journal of the Korea Society of Computer and Information
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• v.14 no.1
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• pp.173-181
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• 2009

This paper proposes an algorithm to transform RDF(Resource Description Framework) models for ontology into CPN(Colored Petri Net) models. The algorithm transforms the semantics of the RDF model into the topology of the CPN by mapping the classes and the properties of the RDF onto the places of the CPN model then reflects the RDF statements on the CPN by representing the relationships between them as token transitions on the CPN. The basic idea of reflecting the RDF statements on the CPN is to generate a token, which is an ordered pair consisting of two tokens (one from the place mapped into the subject and the other one from the place mapped into the object) and transfer it to the place mapped into the predicate. We have actually built CPN models for given RDF models on the CNPTools and inferred and extracted answers to the RDF queries on the CPNTools.