• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.8 no.6
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• pp.491-496
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• 2015

Cloud computing has emerged with promise to decrease the cost of server additional cost and expanding the data storage and ease for computer resource sharing and apply the new technologies. However, Cloud computing also raises many new security concerns due to the new structure of the cloud service models. Therefore, the secure user authentication is required when the user is using cloud computing. This paper, we propose the enhanced AdaBoost algorithm for access cloud security zone. The AdaBoost algorithm despite the disadvantage of not detect a face inclined at least 20, is widely used because of speed and responsibility. In the experimental results confirm that a face inclined at least 20 degrees tilted face was recognized. Using the FEI Face Database that can be used in research to obtain a result of 98% success rate of the algorithm perform. The 2% failed rate is due to eye detection error which is the people wearing glasses in the picture.

• Journal of Internet Computing and Services
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• v.5 no.6
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• pp.79-91
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• 2004

Various facial pose detection and recognition has been a difficult problem. The problem is due to the fact that the distribution of various poses in a feature space is mere dispersed and more complicated than that of frontal faces, This thesis proposes a robust pose-expression-invariant face recognition method in order to overcome insufficiency of the existing face recognition system. First, we apply the TSL color model for detecting facial region and estimate the direction of face using facial features. The estimated pose vector is decomposed into X-V-Z axes, Second, the input face is mapped by deformable template using this vectors and 3D CANDIDE face model. Final. the mapped face is transformed to frontal face which appropriates for face recognition by the estimated pose vector. Through the experiments, we come to validate the application of face detection model and the method for estimating facial poses, Moreover, the tests show that recognition rate is greatly boosted through the normalization of the poses and expressions.

• The KIPS Transactions:PartB
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• v.10B no.6
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• pp.647-656
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• 2003

This paper proposes the system to generate caricature (character's face) resembling human face using extracted facial features automatically. Since this system is vector-based, the generated character's face has no size limit and constraint. So it is available to transform the shape freely and to apply various facial expressions to 2D face. Moreover, owing to the vector file's advantage, it can be used in mobile environment as small file site.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.45 no.1
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• pp.75-83
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• 2008

We propose a welfare interface using multiple fecial features tracking, which can efficiently implement various mouse operations. The proposed system consist of five modules: face detection, eye detection, mouth detection, facial feature tracking, and mouse control. The facial region is first obtained using skin-color model and connected-component analysis(CCs). Thereafter the eye regions are localized using neutral network(NN)-based texture classifier that discriminates the facial region into eye class and non-eye class, and then mouth region is localized using edge detector. Once eye and mouth regions are localized they are continuously and correctly tracking by mean-shift algorithm and template matching, respectively. Based on the tracking results, mouse operations such as movement or click are implemented. To assess the validity of the proposed system, it was applied to the interface system for web browser and was tested on a group of 25 users. The results show that our system have the accuracy of 99% and process more than 21 frame/sec on PC for the $320{\times}240$ size input image, as such it can supply a user-friendly and convenient access to a computer in real-time operation.

• Journal of Broadcast Engineering
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• v.27 no.4
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• pp.519-526
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• 2022

Identifying and searching for characters appearing in scenes during multimedia video editing is an arduous and time-consuming process. Applying artificial intelligence to labor-intensive media editing tasks can greatly reduce media production time, improving the creative process efficiency. In this paper, a method is proposed which combines existing artificial intelligence based techniques to automate character recognition and search tasks for video editing. Object detection, face detection, and pose estimation are used for character localization and face recognition and color space analysis are used to extract unique representation information.

• Journal of KIISE:Software and Applications
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• v.31 no.6
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• pp.817-828
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• 2004

In this paper, we propose vector-based face generation system that uses montage and shading method and preserves designer(artist)'s style. Proposed system generates character's face similar to human face automatically using facial features that extracted from a photograph. In addition, unlike previous face generation system that uses contours, we propose the system is based on color and composes face from facial features and shade extracted from a photograph. Thus, it has advantages that can make more realistic face similar to human face. Since this system is vector-based, the generated character's face has no size limit and constraint. Therefore it is available to transform the shape freely and to apply various facial expressions to 2D face. Moreover, it has distinctiveness with another approaches in point that can keep artist's impression just as it is in result.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.9 no.4
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• pp.75-79
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• 2009

In this paper the method was proposed which uses ${\lambda}$-fuzzy measure to detect the edge of the features of the face region. In the conventional method the features was founded using valley, brightness and edge. This method had its drawbacks that it is so sensitive to the external noises and environments. This paper proposed ${\lambda}$-fuzzy measure to cope with this drawbacks. By considering each weight of the pixels the integral evaluation was considered using the center of area method. Thus the continuity of the edge was kept by way of the neighborhood information and the reduction of time complexity wad resulted in.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.1
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• pp.163-170
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• 2022

This paper introduces a method of extracting facial features due to unrefined inputs in real life and improving the problem of not guaranteeing the ideal performance and speed of the object recognition model through a storage algorithm through weight summation. Many facial recognition processes ensure accuracy in ideal situations, but the problem of not being able to cope with numerous biases that can occur in real life is drawing attention, which may soon lead to serious problems in the face recognition process closely related to security. This paper presents a method of quickly and accurately recognizing faces in real time by comparing feature points extracted as input with a small number of feature points that are not overfit to multiple biases, using that various variables such as picture composition eventually take an average form.

• Journal of KIISE:Software and Applications
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• v.30 no.7_8
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• pp.773-779
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• 2003

Locating exact position of facial components is a key preprocessing for realizing highly accurate and reliable face recognition schemes. In this paper, we propose a simple but powerful method for detecting isolated facial components such as eyebrows, eyes, and a mouth, which are horizontally oriented and have relatively dark gray levels. The method is based on the shape-resolving locally optimum thresholding that may guarantee isolated detection of each component. We show that pure facial regions can be determined by grouping facial features satisfying simple geometric constraints on unique facial structure. In the test for over 1000 images in the AR -face database, pure facial regions were detected correctly for each face image without wearing glasses. Very few errors occurred in the face images wearing glasses with a thick frame because of the occluded eyebrow -pairs. The proposed scheme may be best suited for the later stage of classification using either the mappings or a template matching, because of its capability of handling rotational and translational variations.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.9C
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• pp.1258-1268
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• 2004

We propose a new fast, algorithm which is used for detecting frontal face in the frequency domain based on human skin-color using OCT coefficient of dynamic image compression and skin color information. The region where each pixel has a value of skin-color were extracted from U and V value based on DCT coefficient obtained in the process of Image compression using skin-color map in the Y, U, V color space A morphological filter and labeling method are used to eliminate noise in the resulting image We propose the algorithm to detect fastly human face that estimate the directional feature and variance of luminance block of human skin-color Then Extraction of face was completed adaptively on both background have the object analogous to skin-color and background is simple in the proposed algorithm The performance of face detection algorithm is illustrated by some simulation results earned out on various races We confined that a success rate of 94 % was achieved from the experimental results.