• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.8
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• pp.1809-1818
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• 2010

In order to detect the skin color area from input images, many prior researches have divided an image into the pixels having a skin color and the other pixels. In a still image or videos, it is very difficult to exactly extract the skin pixels because lighting condition and makeup generate a various variations of skin color. In this thesis, we propose a method that improves its performance using hierarchical merging of 3D skin color model and context informations for the images having various difficulties. We first make 3D color histogram distributions using skin color pixels from many YCbCr color images and then divide the color space into 3 layers including skin color region(Skin), non-skin color region(Non-skin), skin color candidate region (Skinness). When we segment the skin color region from an image, skin color pixel and non-skin color pixels are determined to skin region and non-skin region respectively. If a pixel is belong to Skinness color region, the pixels are divided into skin region or non-skin region according to the context information of its neighbors. Our proposed method can help to efficiently segment the skin color regions from images having many distorted skin colors and similar skin colors.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.43 no.3 s.309
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• pp.84-91
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• 2006

In this paper, we present a new segmentation algorithm for color images based on mathematical morphology and a Gaussian mixture model(GMM). We use the morphological operations to determine the number of components in a mixture model and to detect their modes of each mixture component. Next, we have adopted the GMM to represent the probability distribution of color feature vectors and used the deterministic annealing expectation maximization (DAEM) algorithm to estimate the parameters of the GMM that represents the multi-colored objects statistically. Finally, we segment the color image by using posterior probability of each pixel computed from the GMM. The experimental results show that the morphological operation is efficient to determine a number of components and initial modes of each component in the mixture model. And also it shows that the proposed DAEM provides a global optimal solution for the parameter estimation in the mixture model and the natural color images are segmented efficiently by using the GMM with parameters estimated by morphological operations and the DAEM algorithm.

• Journal of the Korean Institute of Intelligent Systems
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• v.24 no.5
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• pp.462-469
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• 2014

As a basic study on both engineering applications and representation methods of synesthesia, this paper aims at building basic system which converts a muscular sense into both visual and auditory elements. As for the building method, data of the muscular sense can be acquired through roll and pitch signals which are calculated from both three-axis acceleration sensor and the two-axis gyro sensor. The roll and pitch signals are then converted into both visual and auditory information as outputs. The roll signals are converted into both intensity elements of the HSI color model and octaves as one of auditory elements. In addition, the pitch signals are converted into both hue elements of the HSI color model and scales as another one of auditory elements. Each of the extracted elements of the HSI color model is converted into each of the three elements of the RGB color model respectively, so that the real-time output color signals can be obtained. Octaves and scales are also converted and synthesized into MIDI signals, so that the real-time sound signals can be obtained as anther one of output signals. In experiments, the results revealed that normal color and sound output signals were successfully obtained from roll and pitch values that represent muscular senses or physical movements, depending on the conversion relationship based on the similarity between color and sound.

• The Journal of the Korea Contents Association
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• v.9 no.4
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• pp.1-11
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• 2009

To classifying and filtering of adult images, in recent the computer vision techniques are actively investigated because rapidly increase for the amount of adult images accessible on the Internet. In this paper, we investigate and develop the tool filtering of adult images using skin color model. The tool is consisting of two steps. In the first step, we use a skin color classifier to extract skin color regions from an image. In the nest step, we use a region feature classifier to determine whether an image is an adult image or not an adult image depending on extracted skin color regions. Using histogram color model, a skin color classifier is trained for RGB color values of adult images and not adult images. Using SVM, a region feature classifier is trained for skin color ratio on 29 regions of adult images. Experimental results show that suggested classifier achieve a detection rate of 92.80% with 6.73% false positives.

• The Journal of the Korea Contents Association
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• v.9 no.12
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• pp.10-18
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• 2009

Color rendition method is necessary for improving the low contrast images which are achieved by PDA, mobile phone camera or PC camera. There are some methods for color rendition. However, after correcting the color, image quality degradations, such as graying-out, halo-artifact and color noise, may occur. In order to overcome these problems, this paper proposes a retinex-based color rendition method. The proposed method uses the HSV color coordinate system to avoid the graying-out, and the advanced image formation model to reduce the halo-artifact in which the image is divided into three components as the global illumination, the local illumination, and reflectance. The experiment results show that the proposed method yields better performance of color correction over the conveniently method.

• The Journal of the Korea Contents Association
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• v.18 no.10
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• pp.431-442
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• 2018

2-dimensional barcode, QR code has been used for containing various information such as image, video, map, and business cards. Currently, a smartphone is used as a QR code scanner, displaying the code and converting it to a standard URL for a website. However, QR codes are not very common in encrypted application and so have a few applications. This paper proposes a new color-code, which integrates the conventional QR code and color design, and can be effectively used in some product certification system. The proposed method exploits the fact that genuine code is produced by CMYK color model, but the counterfeit is captured by RGB color model and during this process, color information of the code is changed. This paper introduces the color matrix model to measure the distortion between genuine code and counterfeit code. By investigating the statistical characteristics of color matrix, an effective detection of print image forgeries are designed. Various experiments with color codes show that the proposed system can be effectively used in product certification systems.

• Journal of Broadcast Engineering
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• v.25 no.4
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• pp.598-608
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• 2020

In this paper, we propose a color correction technique for images acquired through a multi-view camera system for acquiring a 3D model. It is assumed that the 3D volume is captured indoors, and the position and intensity of the light is constant over time. 8 multi-view cameras are used, and converging toward the center of the space, so even if the lighting is constant, the intensity and angle of light entering each camera may be different. Therefore, a color optimization function is applied to a color correction chart taken from all cameras, and a color conversion matrix defining a relationship between the obtained 8 images is calculated. Using this, the images of all cameras are corrected based on the standard color correction chart. This paper proposed a color correction method to minimize the color difference between cameras when acquiring an image using 8 cameras of 3D objects, and experimentally proved that the color difference between images is reduced when it is restored to a 3D image.

• The Research Journal of the Costume Culture
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• v.13 no.5 s.58
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• pp.712-728
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• 2005

This study consists of the stimuli of a female model in her twenties with twenty-three different facial make-up and survey on the differences of them for the development of make-up color system, based on the color-sense on the Korean's skin-tone and make-up color, to enforce the efficiency of beauty education. The result of this study and the suggestion is as followed. Firstly, Familiarity, Intelligence, Fitness, Charm, Tradition and Youth were came out as the result of factor analysis of make-up color image perception. Secondly, the stimulus of bare face was evaluated as more familiar and intelligent than the one with image make-up but perceived as unhealthy and not untraditional. Thirdly, skin tone had a big impact on both in lip color that's been applied in monotonous make-up and in image make-up that had been applied in contrastive make-up. Through these results, it is confirmed that the skin tone and make-up colors were influential variables in the research on facial image perception and preference against a female model in her 20s, and also the image test and preference can be changed according to the color contrasts. This research will be used as a basic tool for the development of make-up color applying system with image perception of statics of population variables and preference research. Also it aims to suggest the alternatives to perform the present collage make-up education for more systematic and organized education.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.3
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• pp.330-335
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• 2004

In this paper, we propose the technique for recognizing the human emotion by using the color image. To do so, we first extract the skin color region from the color image by using HSI model. Second, we extract the face region from the color image by using Eigenface technique. Third, we find the man's feature points(eyebrows, eye, nose, mouse) from the face image and make the fuzzy model for recognizing the human emotions (surprise, anger, happiness, sadness) from the structural correlation of man's feature points. And then, we infer the human emotion from the fuzzy model. Finally, we have proven the effectiveness of the proposed method through the experimentation.

• Journal of Korean Institute of Industrial Engineers
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• v.31 no.1
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• pp.68-78
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• 2005

A new emotion-based image retrieval method is proposed in this paper. The research was motivated by Soen's evaluation of human emotion on color patterns. Thirteen pairs of adjective words expressing emotion pairs such as like-dislike, beautiful-ugly, natural-unnatural, dynamic-static, warm-cold, gay-sober, cheerful-dismal, unstablestable, light-dark, strong-weak, gaudy-plain, hard-soft, heavy-light are modeled by 19-dimensional color array and $4{\times}3$ gray matrix in off-line. Once the query is presented in text format, emotion model-based query formulation produces the associated color array and gray matrix. Then, images related to the query are retrieved from the database based on the multiplication of color array and gray matrix, each of which is extracted from query and database image. Experiments over 450 images showed an average retrieval rate of 0.61 for the use of color array alone and an average retrieval rate of 0.47 for the use of gray matrix alone.