• Journal of Advanced Navigation Technology
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• v.20 no.6
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• pp.625-630
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• 2016

Recently, various types of image contents are being produced, and interest in copyright protection technology is increasing. In this paper, we propose an image encryption technology for color images. This technique divides the image into RGB color components and then performs quad-tree decomposition based on the edge of image. After the quad-tree partitioning, encryption is performed on the selected blocks. Encryption is performed on color components to measure encryption efficiency, and encryption efficiency is measured even after reconstitution into a color image. The encryption efficiency uses a visual measurement method and an objective image quality evaluation method. The PSNR values were measured as 7~10 dB for color difference components and 16~19 dB for color images. The proposed image encryption technology will be used to protect copyright of various digital image contents in the future.

• Proceedings of the IEEK Conference
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• 2001.09a
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• pp.447-450
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• 2001

자동차 번호판 인식 시스템은 크게 세 부분으로 나뉘어 질 수 있는데 그 첫 부분이 Camera를 통해서 획득된 영상에서 번호판 영역을 추출하는 것이다. 본 논문에서는 자가용과 영업용 번호판의 배경이 모두 다른 부분과 차이를 가지고 있다는 점을 이용하여 번호판 영역 추출을 위하여 기존의 방법과 달리 Color 정보를 이용하였다. Edge 검출이나 Gray level의 변화값을 이용하지 않고 Color 정보를 이용함으로써 번호판이 구부러진 영상이나 Noise를 통해서 훼손된 영상, Contrast가 낮은 영상에도 영역 추출에 강한 성능을 나타내었다. Camera를 통해서 획득된 RGB 영상을 YCbCr Format으로 바꾸고 그 중 Cb와 Cr 정보를 이용하여 번호판 영역을 검출하고 인증과정을 거쳐서 추출된 영상이 실제로 번호판 영상인지를 확인하는 단계를 거쳤다. 실험을 통하여 주간, 야간 및 훼손되거나 Noise가 많이 발생한 영상에서도 강한 성능을 나타냄을 볼 수 있었다.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.6
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• pp.1207-1214
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• 2009

In this study, we propose a novel color-image segmentation algorithm to discern the teeth region utilizing RG intensity and its relevant RGB histogram features with resolving the variations of its maximum intensity in terms of peaks and valleys. Tooth candidates in a CCD image are first extracted by applying RGB color multi-threshold levels and consequently the successive morphological image operations and a Sobel-mask edge processing are performed to resolve the teeth region and its contour.

• Journal of the Semiconductor & Display Technology
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• v.12 no.4
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• pp.33-38
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• 2013

Image retrieval is one of the most exciting and fastest growing research fields in the area of multimedia technology. As the amount of digital contents continues to grow users are experiencing increasing difficulty in finding specific images in their image libraries. This paper proposes an efficient image descriptor which uses a local color and texture in the non-overlapped block images. To evaluate the performance of the proposed method, we assessed the retrieval efficiency in terms of ANMRR with common image dataset. The experimental trials revealed that the proposed algorithm exhibited a significant improvement in ANMRR, compared to Dominant Color Descriptor and Edge Histogram Descriptor.

• Proceedings of the IEEK Conference
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• 2003.07e
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• pp.1795-1798
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• 2003

내용을 기반으로 하는 영상검색에 있어 색상과 물체의 특징은 중요한 요소로서, 지금까지의 검색 기법들은 이들을 중심으로 연구가 진행되어 왔으며, 이들을 추출하기 위해서는 color 영상에서의 배경과 물체의 분리는 선행되어야 할 중요한 과제이다. color 영상에서 물체를 분리 하고자 하는 여러 가지 시도가 있었으나, 대부분 clustering 에 준하고 있으며, 처리시간이나 결과에 있어서 그다지 좋은 효과를 내지 못하는 것도 사실이다. 따라서, 영상검색을 위한 물체의 분리 기법으로서는 적합하지 않다. 본 논문에서는 물체가 영상의 중심에 주로 위치한다는 점에 착안한 방법을 응용하여 영상의 외곽에 존재하는 색상뿐만 아니라 명암까지 분석하여, 배경을 구성하는 화소들의 색상 및 명암과 동일하지 않은 색상들로 이루어진 부분을 물체로 판단, 추출하는 기법에 대해 설명하고, edge를 추출해낸 영상의 정보와 합성하여 최적의 물체를 찾아 검색을 하는 기법에 대하여 기술하였다.

• Smart Media Journal
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• v.1 no.4
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• pp.27-34
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• 2012

In this paper, a novel text binarization is presented that can deal with some complex conditions, such as shadows, non-uniform illumination due to highlight or object projection, and messy backgrounds. To locate the target text region, a focus line is assumed to pass through a text region. Next, connected component analysis and stroke width estimation based on location information of the focus line is used to locate the bounding box of the text region, and each box of connected components. A series of classifications are applied to identify whether each CC(Connected component) is text or non-text. Also, a modified K-means clustering method based on an HCL color space is applied to reduce the color dimension. A text binarization procedure based on location of text component and seed color pixel is then used to generate the final result.

• The Journal of the Korea institute of electronic communication sciences
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• v.8 no.3
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• pp.415-420
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• 2013

In recent, many researches have been studying sensitivity and psychology of human on color. Among them, a picture of children can be a tool to represent their emotion. Information of colors and direction on a child's picture often represent his internal psychological states unconsciously. In this paper, we propose the method that extract the color and direction information in order to analyze the psychology in the picture of children. Histogram clustering is used for color information detection. Direction information extract from inner edge value. In the result of experiments, we shows that our method is similar to the pattern classification of the general method.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.48 no.1
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• pp.127-132
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• 2011

In this paper, we propose a novel method of adult image classification by combining skin color regions and edges in an input image. The proposed method consists of four steps. In the first step, initial skin color regions are detected by logical AND operation of all skin color regions detected by the existing methods of skin color detection. In the second step, a skin color probability map is created by modeling the distribution of skin color in the initial regions. Then, a binary image is generated by using threshold value from the skin color probability map. In the third step, after using the binary image and edge information, we detect final skin color regions using a region growing method. In the final step, adult image classification is performed by support vector machine(SVM). To this end, a feature vector is extracted by combining the final skin color regions and neighboring edges of them. As experimental results, the proposed method improves performance of the adult image classification by 9.6%, compared to the existing method.

• Weed & Turfgrass Science
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• v.7 no.2
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• pp.130-139
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• 2018

The colors of packaging of herbicides and non-selective herbicides on the market in Korea are defined as brown and red, respectively, according to the notification of RDA. The present study aimed to understand consumer's electroencephalographic (EEG) response when looking at brown and red colors of herbicide and non-selective herbicide packaging papers. The EEG cap was placed on the scalp of each participant (men and women, 10 to 20 years old) and white (control) - brown - white - red colors were sequentially displayed for 5 seconds using the computer monitor. The EEG was measured and statistical analysis was performed using SPSS. For the brown color of the herbicide, men showed a decrease in concentration and a distracting response due to a decrease in the ratio of mid beta to theta (RMT) and the spectral edge of frequency (SEF90). In women, an increase in the ratio of SMR to theta (RSMT) and the spectral edge frequency 50% of the alpha (ASEF) was observed in different brain regions and these EEG changes may enhance the relaxation, stabilization and awakening states of the brain. For the red color of the non-selective herbicide, ASEF increased psychological stability in men. In women, a decrease in absolute high beta (AHB) may associate with a decrease in attention state of the brain. Overall data of the present study clearly revealed that the colors of two herbicides showed significantly different EEG response and gender difference.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.9
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• pp.119-126
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• 2013

In this paper, we propose a chromatic aberration removal algorithm in image capture devices, which considers local properties of the image. Chromatic aberration is generated by the fact that the refractive index of the lens is different for different wavelengths, which produces color artifacts on strong edge due to misalignment of RGB channels. Under the characteristics of the artifacts, the proposed algorithm first estimates the regions with the apparent color artifacts as the neighborhoods of the strong edge. In the regions, the proposed algorithm removes the color artifacts by matching the edges of RGB channels. The widely used conventional methods based on global image warping could not remove the color artifacts of longitudinal chromatic aberration and purple fringing identified by the image sensor, whereas the matching process of the proposed method could reduce them. Experimental results show that the proposed algorithm outperforms the conventional methods on objective and subjective criteria.