• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2003.10a
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• pp.691-694
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• 2003

This paper proposes an 3D face image watermarking method based on discrete wavelet transform(DWT). First, 3D face image are transformed by DWT and inserted gaussian watermark into frequency domain. To increase the robustness and perceptual invisibility of watermark, the proposed algorithm is combined with the characteristics of 3D face image and human visual system. The proposed method is invisible and blind watermarking which the original image is not required. Simulation results show that the proposed method is robust to the general attack such as JPEG compression, enhancement, noise, cropping, and filtering etc.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1993.06a
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• pp.1309-1312
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• 1993

We present a flexible retrieval system of face photographs based on their linguistic descriptions in terms of fuzzy perdicates. While natural for describing a face, linguistic expressions are also subjective, which affects the retrieval result. Thus, the capability of a retrieval system to adjust to different users becomes very important. In this research we use fuzzy logic techniques, for describing image data, inference for retrieval and adjustment to a new user. Experimental results of the adjustment are also included.

• Journal of the Korean Institute of Intelligent Systems
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• v.13 no.4
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• pp.403-408
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• 2003

A general meaning of caricaturing is that a representation, especially pictorial or literary, in which the subject's distinctive features or peculiarities are deliberately exaggerated to produce a comic or grotesque effect. In other words, a caricature is defined as a rough sketch(dessin) which is made by detecting features from human face and exaggerating or warping those. There have been developed many methods which can make a caricature image from human face using computer. In this paper, we propose a new caricaturing system. The system uses a real-time image or supplied image as an input image and deals with it on four processing steps and then creates a caricatured image finally. The four Processing steps are like that. The first step is detecting a face from input image. The second step is extracting special coordinate values as facial geometric information. The third step is deforming the face image using local warping method and the coordinate values acquired in the second step. In fourth step, the system transforms the deformed image into the better improved edge image using a fuzzy Sobel method and then creates a caricatured image finally. In this paper , we can realize a caricaturing system which is simpler than any other exiting systems in ways that create a caricatured image and does not need complex algorithms using many image processing methods like image recognition, transformation and edge detection.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.31B no.9
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• pp.101-111
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• 1994

The human face can provide a great deal of information in regard to his/her race, age, sex, personality, feeling, psychology, mental state, health condition and ect. If we pay a close attention to the aging process, we are able to find out that there are recognizable phenomena such as eyelid drooping, cheek drooping, forehead furrowing, hair falling-out, the hair becomes gray and etc. This paper proposes that the method to estimate the age by analyzing these feature components for the facial image. Ang we also introduce the method of facial image synthesis in accordance with the cange of age. The feature components according to the change of age can be obtainec by dividing the facial image into the 3-dimensional shape of a face and the texture of a face and then analyzing the principle component respectively using 3-dimensional model. We assume the age of the facial image by comparing the extracted feature component to the facial image and synthesize the resulted image by adding or subtracting the feature component to/from the facial image. As a resurt of this simulation, we have obtained the age changed ficial image of high quality.

• International Journal of Costume and Fashion
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• v.6 no.2
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• pp.11-27
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• 2006

The purpose of this study is to develop highly valued fashion cultural items using Korean face and human images to enhance global competition. The methods of this study include: historical study on the face/human images which appear on the dress; design by stage according to Lamb & Kallal's apparel design process; development of products using digital textile printing technology; and case study by objective evaluation through Grant's alpha-beta model. The procedure and the results of this study are as follows: First, in the problem identification stage, the need to develop fashion cultural products of Korean face/human images which are symbolic, aesthetic, and functional was recognized in order to enhance global competition. Second, in the preliminary idea stage, the fashion cultural products and the components that meet the above 3 standards for design were determined and first design was drawn up. The source of the design was extrapolated from face/human images, which appeared on the murals of the ancient Korea, the portraits and custom paintings from the Chosun Dynasty. From these images, a total of 7 design series of T-shirts with an "ULGUL" logo, scarves, and artwalls were developed using "obangsaek" which are five Korean traditional colors including red, blue, black. white, and yellow on cottons and silks. Third, in the design refinement stage, based on the preference survey, more varying design methods were used to develop 25 new designs. Fourth, in prototype development stage, based on the preference survey conducted on fashion professionals and general public from the previous stage, which showed preference for T-shirts and scarves, 3 designs on T-shirts and 2 designs on scarves were printed and produced using the DTP (Digital Textile Printing). Fifth, in the evaluation stage, Grant's alpha-beta model was used to perform comparative evaluation on the symbolic, aesthetic, and functional criteria of the new designs over the existing ones. The new designs received excellent results in all three criteria and a special recognition was given to symbolism of the new designs.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.31B no.7
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• pp.119-128
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• 1994

In this paper, we propose a method for facial feature extraction and recognition algorithm using neural networks. First we extract a face part from the background image based on the knowledge that it is located in the center of an input image and that the background is homogeneous. Then using vertical and horizontal projections. We extract features from the separated face image using knowledge base of human faces. In the recognition step we use the back propagation algorithm of the neural networks and in the learning step to reduce the computation time we vary learning and momentum rates. Our technique recognizes 6 women and 14 men correctly.

• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.3037-3040
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• 2000

Real-Time object tracking has emerged as an important component in several application areas including machine vision. surveillance. Human-Computer Interaction. image-based control. and so on. And there has been developed various algorithms for a long time. But in many cases. they have showed limited results under uncontrolled situation such as illumination changes or cluttered background. In this paper. we present a novel. computationally efficient algorithm for tracking human face robustly under illumination changes and cluttered backgrounds. Previous algorithms usually defines color model as a 2D membership function in a color space without consideration for illumination changes. Our new algorithm developed here. however. constructs a 3D color model by analysing plenty of images acquired under various illumination conditions. The algorithm described is applied to a mobile head-eye robot and experimented under various uncontrolled environments. It can track an human face more than 100 frames per second excluding image acquisition time.

• Proceedings of the KIEE Conference
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• 2006.10c
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• pp.214-216
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• 2006

Expressive face and human body gestures are among the main non-verbal communication channels in human-human interaction. Understanding human emotions through body gesture is one of the necessary skills both for humans and also for the computers to interact with their human counterparts. Gesture analysis is consisted of several processes such as detecting of hand, extracting feature, and recognizing emotions. Skin color information for tracking hand gesture is obtained from face detection region. We have revealed relationships between paricular body movements and specific emotions by using HMM(Hidden Markov Model) classifier. Performance evaluation of emotional human body recognition has experimented.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.6
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• pp.783-788
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• 2004

Many reported methods assume that the faces in an image or an image sequence have been identified and localization. Face detection from image is a challenging task because of the variability in scale, location, orientation and pose. The difficulties in visual detection and recognition are caused by the variations in viewpoint, viewing distance, illumination. In this paper, we present an efficient linear discriminant for multi-view face detection and face location. We define the training data by using the Fisher`s linear discriminant in an efficient learning method. Face detection is very difficult because it is influenced by the poses of the human face and changes in illumination. This idea can solve the multi-view and scale face detection problems. In this paper, we extract the face using the Fisher`s linear discriminant that has hierarchical models invariant size and background. The purpose of this paper is to classify face and non-face for efficient Fisher`s linear discriminant.

• Journal of Internet Computing and Services
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• v.4 no.6
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• pp.57-67
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• 2003

The recent rapid development of multimedia and optical technologies brings great attention to application systems to process facial Image features. The previous research efforts in facial image processing have been mainly focused on the recognition of human face and facial expression analysis, using front face images. Not much research has been carried out Into image-based detection of face direction. Moreover, the existing approaches to detect face direction, which normally use the sequential Images captured by a single camera, have limitations that the frontal image must be given first before any other images. In this paper, we propose a method to detect face direction by using facial features such as facial trapezoid which is defined by two eyes and the lower lip. Specifically, the proposed method forms a facial direction formula, which is defined with statistical data about the ratio of the right and left area in the facial trapezoid, to identify whether the face is directed toward the right or the left. The proposed method can be effectively used for automatic photo arrangement systems that will often need to set the different left or right margin of a photo according to the face direction of a person in the photo.