• Journal of the Institute of Convergence Signal Processing
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• v.6 no.1
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• pp.15-22
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• 2005

In this paper, we propose a face recognition system by using the CCD color image. We first get the face candidate image by using YCbCr color model and adaptive skin color information. And we use it initial curve of active contour model to extract face region. We use the Eye map and mouth map using color information for extracting facial feature from the face image. To obtain center point of Log-polar image, we use extracted facial feature from the face image. In order to obtain feature vectors, we use extracted coefficients from DCT and wavelet transform. To show the validity of the proposed method, we performed a face recognition using neural network with BP learning algorithm. Experimental results show that the proposed method is robuster with higher recogntion rate than the conventional method for the rotation and scale variant.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.12C
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• pp.1686-1691
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• 2004

In this paper, we present an improved method to calculate Euclidean distance transform based on Guan's method. Compared to the conventional method, Euclidean distance can be computed faster using Guan's method when the number of feature pixels is small; however, overall computational cost increases proportional to the number of feature pixels in an image. To overcome this problem, we divide feature pixels into two groups: boundary feature pixels (BFPs) and non-boundary feature pixels (NFPs). Here BFPs are defined as those in the 4-neighborhood of foreground pixels. Then, only BFPs are used to calculate the Voronoi diagram resulting in a Euclidean distance map. Experimental results indicate that the proposed method takes 40 Percent less computing time on average than Guan's method. To prove the performance of the proposed method, the computing time of Euclidean distance map by proposed method is compared with the computing time of Guan's method in 16 images that are binary and the size of 512${\times}$512.

• (The) Research of the performance art and culture
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• no.22
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• pp.45-61
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• 2011

Performers of 'Seoul Jinjinokigut' point to aesthetics of performance centered on sense of sight, not sense of hearing. 'Seoul Jinjinokigut' is a kind of theatrical mode of performance, not narrative mode of performance. Performers of 'Seoul Jinjinokigut' succeed in making of relationships of harmonious fusion between 'social drama' and 'stage drama' through performing of Jinjinokigut. 'Seoul Jinjinokigut' is a kind of mode of performance that fuses life and death, not narratively but theatrically.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.43 no.12 s.354
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• pp.16-23
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• 2006

This paper presents the development of the fast Direction Finder using direct conversion method, which can intercept for short pulse signal of less' than 1 msec. in RF Down Converter, and CVDF(Correlative Vector Direction Finding) algorithm, which estimates DoA (Direction of Arrival). The configuration and characteristics of direction finder using 5-channel equi-spaced circular array antenna are presented and the direct conversion techniques for removing tuning time using I/Q demodulator are described. The CRLB of our model is derived, the principles of 2 kind of CVDF algorithm are explained and their characteristics are compared with CRLB w.r.t the number of samples and spacing ratio. The RF Down Converter prototype using direct conversion method is manufactured, the 2 kind of CVDF algorithm are applied and their performance are analyzed. Finally it is confirmed the LSE based CVDF algorithm is better than correlation-coefficient based except for ambiguity protection capabilities.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.10C
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• pp.1414-1424
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• 2004

In this paper, an algorithm using wavelet transform for detecting a cut that is a radical scene transition point, and fade and dissolve that are gradual scene transition points is proposed. The conventional methods using wavelet transform for this purpose is using features in both spatial and frequency domain. But in the proposed algorithm, the color space of an input image is converted to YUV and then luminance component Y is transformed in frequency domain using 2-level lifting. Then, the histogram of only low frequency subband that may contain some spatial domain features is compared with the previous one. Edges obtained from other higher bands can be divided into global, semi-global and local regions and the histogram of each edge region is compared. The experimental results show the performance improvement of about 17% in recall and 18% in precision and also show a good performance in fade and dissolve detection.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• v.9 no.2
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• pp.451-454
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• 2005

Recently, many methods to analyze signal have been proposed and representative methods are the Fourier transform and wavelet transform. In these methods, the Fourier transform represents signal with combination cosine and sine at all locations in the frequency domain. However, it doesn't provide time information that particular frequency occurs in signal and depends on only the global feature of the signal. So, to improve these points the wavelet transform which is capable of multiresolution analysis has been applied to many fields such as speech processing, image processing and computer vision. And the wavelet transform, which uses changing window according to scale parameter, presents time-frequency localization. In this paper, we proposed a new approach using a wavelet of cosine and sine type and analyzed features of signal in a limited point of frequency-time plane.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.7
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• pp.896-902
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• 2021

Rotated face detection is required in many applications but still remains as a challenging task, due to the large variations of face appearances. In this paper, a polar coordinate transform that is not affected by rotation is proposed. In addition, a method for effectively detecting rotated faces using the transformed image has been proposed. The proposed polar coordinate transform maintains spatial information between facial components such as eyes, mouth, etc., since the positions of facial components are always maintained regardless of rotation angle, thereby eliminating rotation effects. Polar coordinate transformed images are trained using AdaBoost, which is used for frontal face detection, and rotated faces are detected. We validate the detected faces using LBP that trained the non-face images. Experiments on 3600 face images obtained by rotating images in the BioID database show a rotating face detection rate of 96.17%. Furthermore, we accurately detected rotated faces in images with a background containing multiple rotated faces.

• Proceedings of the Korea Multimedia Society Conference
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• 2002.11b
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• pp.381-384
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• 2002

본 논문에서는 실험 영상으로부터 학습된 피부색상 정보를 이용하여 컬러 공간테이블을 생성한 후. 입력된 영상의 컬러와 공간정보를 학습된 피부색상 공간테이블로부터 비교, 분석하여 얼굴후보영역을 찾고자 하였다. 또한 추출된 후보영역의 레이블된 특징정보를 이용하여 지역적 특징을 찾아낸 후 얼굴 특징점의 위치에 따른 형태정보를 이용하여 신뢰할 수 있는 얼굴 영역을 검출하고자 하였다. 제안된 피부색상(Skin-tone)공간테이블은 변환하기 쉽고 계산이 빠른 RGB컬러 공간에서 실험, 평가되었으며, 실시간으로 입력된 영상의 정규화된 책상 값을 유사성 정도에 따라 레이블링하여 보다 빠른 얼굴 후보 영역의 검출과 검증을 할 수 있도록 하였다.

• Proceedings of the Korean Information Science Society Conference
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• 2003.10b
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• pp.592-594
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• 2003

이 논문에서는 wavelet과 sobel filter를 사용하여 영상의 객관적인 평가 점수를 계산하는 새로운 기법을 제안한다. 이 기법은 orthogonal wavelet 변환을 기초로 하고 있으며 원본 영상과 처리된 영상 데이터가 모두 가용하다는 것을 전제로 한다. Wavelet을 이용해 주파수에 따라 분할된 영상 정보를 이용해 각각의 부영역 별 차영상을 획득하고 이 획득된 영상의 에너지를 이용해 화질 평가 수치를 계산한다. 부영역 별로 획득된 영상은 일정한 크기의 블록으로 분할되어 동일한 블록 내에서 가용한 영상의 특징에 관한 정보(contrast, edge 영역의 분포 정도) 벡터와 내적하여 새로운 특징 벡터로 사용되고, 이 특징 벡터의 가중치를 최적화하여 높은 상관도의 화질평가 점수를 산출하게 된다.

• Journal of KIISE:Databases
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• v.30 no.2
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• pp.125-133
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• 2003

In this paper we propose an efficient content-based image retrieval method using the color and wavelet based texture features. The color features are obtained from soft-color histograms of the global image and the wavelet-based texture features are obtained from the invariant moments of the high-pass sub-band through the spatial-frequency analysis of the wavelet transform. The proposed system, called a color and texture based two-step retrieval(CTBTR), is composed of two-step query operations for an efficient image retrieval. In the first-step matching operation, the color histogram features are used to filter out the dissimilar images quickly from a large image database. The second-step matching operation applies the wavelet based texture features to the retained set of images to retrieve all relevant images successfully. The experimental results show that the proposed algorithm yields more improved retrieval accuracy with computationally efficiency than the previous methods.