• Journal of the Institute of Electronics Engineers of Korea SC
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• v.48 no.5
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• pp.37-44
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• 2011

This paper proposes a confusion-line separating algorithm in a CIE Lab color space using color segmentation for protanopia and deuteranopia. Images are segmented into regions by grouping adjacent pixels with similar color information using the hue components of the images. To this end, the region growing method and the seed points used in this method are the pixels that correspond to peak points in hue histograms that went through a low pass filter. In order to establish a color vision deficiency (CVD) confusion line map, we established 512 virtual boxes in an RGB 3-D space so that boxes existing on the same confusion line can be easily identified. After that, we checked if segmented regions existed on the same confusion line and then performed color adjustment in an CIE Lab color space so that all adjacent regions exist on different confusion lines in order to provide the best color identification effect to people with CVDs.

• Proceedings of the Korea Information Processing Society Conference
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• 2008.05a
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• pp.95-98
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• 2008

본 논문은 기존의 질감기반 (texture) 얼굴검출 시스템에서 컬러 영상을 도입하여 성능개선의 중요한 부분인 얼굴 오검출율을 줄이는 방법을 제안한다. 얼굴 영상의 컬러 성분은 흑백 성분과 비교하여 낮은 공간 주파수 영역을 가지는 특징이 있다. 질감기반 얼굴검출에서 높은 대비 (contrast) 성분의 에지는 얼굴이 아닌 영역에서 얼굴로 오인할 수가 있다. 본 논문에서는 이런 오인을 감소하기 위해 독립적인 컬러 채널 성분들을 질감기반 얼굴 검출에 각각 이용하여 그 얻어진 결과들을 융합 (fusion) 하는 방법을 제안한다. 실험결과로 제안한 칼라 채널 융합 방법을 통해 얻은 얼굴 검출율은 기존 흑백 영상과 비슷하게 유지되며 오검출율을 현저히 줄이는 것을 보였다.

• Journal of the Korea Society of Computer and Information
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• v.19 no.3
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• pp.37-43
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• 2014

In this paper, we propose a robust lip detection algorithm using color clustering. At first, we adopt AdaBoost algorithm to extract facial region and convert facial region into Lab color space. Because a and b components in Lab color space are known as that they could well express lip color and its complementary color, we use a and b component as the features for color clustering. The nearest neighbour clustering algorithm is applied to separate the skin region from the facial region and K-Means color clustering is applied to extract lip-candidate region. Then geometric characteristics are used to extract final lip region. The proposed algorithm can detect lip region robustly which has been shown by experimental results.

• Journal of Korea Multimedia Society
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• v.8 no.4
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• pp.473-481
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• 2005

In this paper, we propose an image segmentation method preserving object's boundaries by using the number of quantized colors and merging regions using adaptive threshold values. First of all, the proposed method quantizes an original image by a vector quantization and the number of quantized colors is determined differently using PSNR each image. We obtain initial regions from the quantized image, merge initial regions in CIE Lab color space and RGB color space step by step and segment the image into semantic regions. In each merging step, we use color distance between adjacent regions as similarity-measure. Threshold values for region-merging are determined adaptively according to the global mean of the color difference between the original image and its split-regions and the mean of those variations. Also, if the segmented image of RGB color space doesn't split into semantic objects, we merge the image again in the CIE Lab color space as post-processing. Whether the post-processing is done is determined by using the color distance between initial regions of the image and the segmented image of RGB color space. Experiment results show that the proposed method splits an original image into main objects and boundaries of the segmented image are preserved. Also, the proposed method provides better results for objective measure than the conventional method.

• Journal of Satellite, Information and Communications
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• v.8 no.3
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• pp.52-57
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• 2013

This paper describes the color comparison analysis of flame in each standard color model in order to propose the optimal color model for image processing based flame detection algorithm. Histogram intersection values were used to analyze the separation characteristics between color of flame and color of non-flame in each standard color model which are RGB, YCbCr, CIE Lab, HSV. Histogram intersection value in each color model and components is evaluated for objective comparison. The analyzed result shows that YCbCr color model is the most suitable for flame detection by average HI value of 0.0575. Among the 12 components of standard color models, each Cb, R, Cr component has respectively HI value of 0.0433, 0.0526, 0.0567 and they have shown the best flame separation characteristics.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.9
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• pp.4472-4477
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• 2013

This paper describes the color features of smoke in each standard color model in order to present the most suitable color model for somke detection in video surveillance system. Histogram intersection technique is used to analyze the difference characteristics between color of smoke and color of non smoke. The considered standard color models are RGB, YCbCr, CIE-Lab, HSV, and if the calculated histogram intersection value is large for the considered color model, then the smoke spilt characteristics are not good in that color model. If the calculated histogram intersection value is small, then the smoke spilt characteristics are good in that color model. The analyzed result shows that the RGB and HSV color models are the most suitable for color model based smoke detection by performing respectively 0.14 and 0.156 for histogram intersection value.

• The Optical Journal
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• v.2 no.9 s.9
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• pp.36-39
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• 1990

• Proceedings of the Korean Information Science Society Conference
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• 2006.06b
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• pp.55-57
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• 2006

본 논문에서는 컬러코드를 이용하여 증강현실 시스템에 사용 가능한 태그를 탐지하는 알고리즘을 설계하고 차단 현상에 강인한 알고리즘을 제안하였다. 기존의 ARToolkit에서 태그의 일부분이 사용자 또는 다른 물체에 의해 가려지게 될 경우 증강되었던 객체가 순간 사라져 버리는 불안정성 (Instability) 문제를 해결하기 위한 방법에 초점을 맞춘다. 불안정성의 문제는 이미지 안에 태그가 존재하지만 해당하는 객체를 증강시키지 못하는 False Negative 에러와 태그가 존재하지 않는 곳에 잘못된 객체를 증강시키는 False Positive 에러로 분류 될 수 있다. 제안된 탐지 알고리즘으로 특정 컬러 영역을 분리하여 모서리 여부를 판별하고 모서리인 경우 가려진 꼭지점의 위치를 추출하여 태그가 차단에 의하여 가려졌을 때에도 객체를 안정적으로 증강시킬 수 있다. 기존 AR 시스템들의 태그를 가지고 Daylight 65, Illuminant A. CWF, TL84의 4가지의 표준 조명하에 컬러코드 4종류, ARToolkit 태그 4개, ARTag 4개를 이용하여 실험을 진행하여 차단 현상이 발생하면 전혀 객체를 증강시킬 수 없었던 ARToolkit에서도 DayLight65의 경우 50%의 False Negative. False Positive rate을 보여 기존 증강현실 시스템에서 보였던 불안정성 문제를 개선하였다.

• Journal of Advanced Navigation Technology
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• v.14 no.2
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• pp.191-197
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• 2010

Many does an application and application but the image analysis of face detection considerably is difficult. In order for with effect of the illumination which is irregular in the present paper America the illumination to range evenly in the face which is detected, detects a face territory, Complemented the result which detects only the front face of existing. With LAB color illumination revisions compared in Adaboost face detection of existing and 32% was visible the face detection result which improves. Bought two images which are input and executed Glassfire label rings. Compared Area critical price and became the area of above critical value and revised from RGB smooth anger and LAB images with LCFD system algorithm. The operational conversion image which is extracted like this executed a face territory detection in the object. In order to extract the feature which is necessary to a face detection used AdaBoost algorithms. The face territory remote login with the face territory which tilts in the present paper, until Multi-view face territory detections was possible. Also relationship without high detection rate seems in direction of illumination, With only the public PC application is possible was given proof user authentication field etc.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 1999.12a
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• pp.575-580
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• 1999