• Journal of the Korean Institute of Intelligent Systems
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• v.11 no.9
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• pp.822-826
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• 2001

The statistical analysis of the feature extraction and the neural networks are proposed to recognize a human face. In the preprocessing step, the normalized skin color map with Gaussian functions is employed to extract the region of face candidate. The feature information in the region of the face candidate is used to detect the face region. In the recognition step, as a tested, the 120 images of 10 persons are trained by the backpropagation algorithm. The images of each person are obtained from the various direction, pose, and facial expression. Input variables of the neural networks are the geometrical feature information and the feature information that comes from the eigenface spaces. The simulation results of 10 persons show that the proposed method yields high recognition rates.

• Journal of the Institute of Electronics and Information Engineers
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• v.53 no.6
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• pp.110-121
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• 2016

The primary aim of the color constancy algorithm is to estimate illuminant chromaticity. There are various statistical-based, learning-based and combinational-based color constancy algorithms already exist. However, the statistical-based algorithms can only perform well on images that satisfy certain assumptions, learning-based methods are complex methods that require proper preprocessing and training data, and combinational-based methods depend on either pre-determined or dynamically varying weights, which are difficult to determine and prone to error. Therefore, this paper presents a new optimization based illuminant estimation method which is free from complex preprocessing and can estimate the illuminant under different environmental conditions. A strong color cast always has an odd standard deviation value in one of the RGB channels. Based on this observation, a cost function called the degree of illuminant tinge(DIT) is proposed to determine the quality of illuminant color-calibrated images. This DIT is formulated in such a way that the image scene under standard illuminant (d65) has lower DIT value compared to the same scene under different illuminant. Here, a swarm intelligence based particle swarm optimizer(PSO) is used to find the optimum illuminant of the given image that minimizes the degree of illuminant tinge. The proposed method is evaluated using real-world datasets and the experimental results validate the effectiveness of the proposed method.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.45 no.4
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• pp.50-58
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• 2008

In this paper, we propose a color transient improvement (CTI) algorithm based on image fusion to improve the color transient in the television(TV) receiver or in the MPEG decoder. Video image signals are composed of one luminance and two chrominance components, and the chrominance signals have been more band-limited than the luminance signals since the human eyes usually cannot perceive changes in chrominance over small areas. However, nowadays, as the advanced media like high-definition TV(HDTV) is developed, the blurring of color is perceived visually and affects the image quality. The proposed CTI method improves the transient of chrominance signals by exploiting the high-frequency information of the luminance signal. The high-frequency component extracted from the luminance signal is modified by spatially adaptive weights and added to the input chrominance signals. The spatially adaptive weight is estimated to minimize the ${\iota}_2-norm$ of the error between the original and the estimated chrominance signals in a local window. Experimental results with various test images show that the proposed algorithm produces steep and natural color edge transition and the proposed method outperforms conventional algorithms in terms of both visual and numerical criteria.

• Journal of Korea Multimedia Society
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• v.13 no.8
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• pp.1142-1153
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• 2010

Conjunctival injection is the initial symptom of various eye diseases such as conjunctivitis, keratitis, or uveitis. The quantification of conjunctival injection may help the diagnosis and follow-up evaluation of various eye diseases. The size of the sclera is an important factor for the quantification of conjunctival injection. However, previous manual segmentation is time-consuming.Automatic segmentation is needed to extract the objective region of interest. This paper proposed a method based on the level set algorithm to segment the sclera from an anterior eye image. The initial model of the level set algorithm is calculated using the Lab color space, k-means algorithm and the geometric information. The level set algorithm was applied to the images in which the valley between the eyeball and skin was enhanced using the hessian analysis. This algorithm was tested with 52 images of the anterior eye segment. Results showed that the proposed method performs better than those with the level set algorithm using an arbitrary circle, or the region growing algorithm with color information. The proposed method for the segmentation of sclera may become an important component for the objective measurement of the conjunctival injection.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.10a
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• pp.93-96
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• 2015

The aim of the estimation of disparity map is to find the corresponding pixels from similar two or more images. However, it is a difficult problem to get precise and consistent disparity under a variety of real world situations. In other words, the color values of stereo images are easily influenced by radiometric properties such as illumination direction, illumination color, and camera exposure. Therefore, conventional stereo matching methods can have low performances under radiometric conditions. In this paper, we propose an approaching of disparity map estimation that is reliable in controlling various radiometric variations close to the real environment. This method is motivated by following constancy. Even though each other has different radiometric property in stereo images, intensity of pixels of object have general constancy in specific block. Experimental results show that the proposed method has better performances compared to the comparison group under different radiometric conditions between stereo images. Consequentially, the proposed method is able to estimate the disparity map in stable under various radiometric variations.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.450-452
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• 2022

Recently, various machine learning algorithms have been actively applied to the field of livestock research, including genetic analysis, and have drawn noteworthy results. In this study, the statistical characteristics of meat color, hydrogen ion concentration, water holding capacity (WHC), shear force, and grilling loss that affect the quality of Hanwoo beef are examined using the Hanwoo beef data collected in various environments. Moreover, the prediction of meat quality is also investigated using the two machine learning algorithms, which are linear regression and regression tree. Analysis results show that meat color has the most significant effect on WHC, which determines the tenderness of beef, and hydrogen ion concentration significantly influences shear force and grilling loss. Through this study, we can confirm the applicability of machine learning algorithms in the research on the quality of Hanwoo beef. In addition, this study can also be applied to the prediction and improvement of the quality of Hanwoo beef.

• The Journal of the Korea Contents Association
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• v.7 no.4
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• pp.250-258
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• 2007

Typography is the combination of language of formative art. It is indeed the core means of human communication through understanding of language and formative values. Studies began on introduction of various techniques to overcome the phenomenon of the 'reaction of language', which appears as an impediment in delivery and sharing of information as the most fundamental roles. Successively, mobile printing types more readable and effective in delivering of meanings have been developed, thus widely distributed for general use. However, although such printing types might be easily used in image and digital media, such as in computer monitors, screens and mobile phone LCDs, etc., it is in fact difficult to use these printing types in printed surfaces, the traditional medium of information delivery, or in sign systems frequently encountered in our surrounding environment. As a solution for this, it is intended to create an effect of communication closer to dynamic typography expression by approaching visual message delivery system from the essence and substance of the color application, which corresponds to the visual spatial expression effect, the core element of expression in dynamic typography to possess significantly more powerful effect in terms of both message delivery capacity and readability than the conventional means of static typography.

• Journal of KIISE:Information Networking
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• v.31 no.5
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• pp.469-481
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• 2004

Previous works for the AF(Assured Forwarding) service in the Diffserv network have no sufficient consideration on the fairness of bandwidth share based on RTTs, the target rates, and the impact of UDP against TCP. In this paper, in order to solve these problems, we propose a FDSA(Fair Differentiated Service Architecture) composed of TRA3CM(Target rate and RTT Aware 3 Color Marking) and TRBD(Target Rate Based Dropping) mechanisms. The TRA3CM and TRBD mechanisms provide three color marking and fair transmission rates among aggregate flows by considering RTT, target rate, and UDP flows simultaneously. In the results of comparing the performance among existing mechanisms and the TRA3CM-TRBD, the TRA3CM-TRBD mechanism was able to mitigate the RTT and UDP effect better than the former. The TRA3CM-TRBD is shown to provide good performance for transmission rates proportional to various target rates.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.11
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• pp.403-409
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• 2016

Recently, harmful content (such as images and photos of nudes) has been widely distributed. Therefore, there have been various studies to detect and filter out such harmful image content. In this paper, we propose a new method using Haar-like features and an AdaBoost algorithm for robustly extracting navel areas in a color image. The suggested algorithm first detects the human nipples through color information, and obtains candidate navel areas with positional information from the extracted nipple areas. The method then selects real navel regions based on filtering using Haar-like features and an AdaBoost algorithm. Experimental results show that the suggested algorithm detects navel areas in color images 1.6 percent more robustly than an existing method. We expect that the suggested navel detection algorithm will be usefully utilized in many application areas related to 2D or 3D harmful content detection and filtering.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.41 no.6
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• pp.61-71
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• 2004

Recently, various techniques for face detection are studied, but most of them still have problems on processing in real-time. Therefore, in this paper, we propose novel techniques for real-time detection of human faces in sequential images using motion and chroma information. First, background model is used to find a moving area. In this procmoving area. edure, intensity values for reference images are averaged, then skin-color are detected in We use HCr color-space model and adaptive threshold method for detection. Second, binary image labeling is applied to acquire candidate regions for faces. Candidates for mouth and eyes on a face are obtained using differences between green(G) and blue(B), intensity(I) and chroma-red(Cr) value. We also considered distances between eye points and mouth on a face. Experimental results show effectiveness of real-time detection for human faces in sequential images.