• Journal of the Korean Institute of Telematics and Electronics S
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• v.35S no.6
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• pp.81-87
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• 1998

This paper proposes an efficient face recognition system using phase difference between the face images. We use a Karhunen-Loeve transform for image compression and reconstruction, and obtain the phase difference by using normalized inner product of the two compressed images. The proposed system is rotation and light-invariant due to using the normalized phase difference, and somewhat shift-invariant due to applying the cosine function. The faster recognition than the conventional system and incremental training is possible in the proposed system. Simulations are conducted on the ORL images of 40 persons, in which each person has 10 facial images, and the result shows that the faster recognition than conventional recognizer using convolution network under the same recognition error rate of 8% does.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.15 no.1
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• pp.58-70
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• 1990

This paper describes a VLSI implementation of real-time two dimensional DCT processor for the subprimary rate video codec system. The proposed architecture exploits the parallelism and concurrency of the distributes architecture for vector inner product operation of DCT and meets the CCITT performance requirements of video codec for full CSIF 30 frames/sec. It is also shown that this architecture satisfies all the CCITT IDCT accuracy specification by simulating the suggested architecture in bit level. The efficient VLSI disign methodology to design suggested architecture is considered and the module generator oriented design environments are constructed based on SUN 3/150C workstation. Using the constructed design environments. the suggensted architecture have been designed by double metal 2micron CMOS technology. The chip area fo designed 8x8 2-D DA-DCT (Distributed Arithmetic DCT) processor is about 3.9mmx4.8mm.

• Journal of the Korea Society of Computer and Information
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• v.15 no.5
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• pp.33-38
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• 2010

In this paper, we proposed an algorithm implementing mouse functions using hand motion and number of fingers which are extracted from an image sequence. The sequence is acquired through a web camera and processed with image processing algorithms. The sequence is first converted from RGB model to YCbCr model to efficiently extract skin area and the extracted area is further processed using labeling, opening, and closing operations to decide the center of a hand. Based on the center position, the number of fingers is decided, which serves as the information to decide and perform a mouse function. Experimental results show that 94.0% of pointer moves and 96.0% of finger extractions are successful, which opens the possibility of further development for a commercial product.

• Proceedings of the Korea Water Resources Association Conference
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• 2017.05a
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• pp.71-71
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• 2017

하천에서 평수기 유량측정은 도섭법을 이용하기 위한 지점식 측정보다는 초음파 도플러 유속계(ADCP, Acoustic Doppler Current Profiler)를 보트에 탑재하여 운용하는 측정 방식이 점차 일반화되고 있다. ADCP는 초음파의 도플러효과를 이용하여 수심이나 횡방향의 유속 분포를 측정할 수 있는 측정 장비로 일반적으로 사용되는 down-looking ADCP는 수심방향의 유속분포와 수심을 측정하여 보트의 이동속도와의 벡터 내적을 이용하여 유량을 산정하게 된다. 그러나, 이동식 ADCP 유량 측정 성과의 불확도는 제공되지 않고 있는 상황인데, 이는 불확도 산정 표준안 미비, 유속 및 수심 등 측정 요소의 관측 환경 별 불확도 정보 부족, 불확도를 산정할 수 있는 툴의 부재 등에 기인한다. 본 연구에서는 이동식 ADCP 불확도 산정 표준안을 개발하고 현장 실험을 통해 불확도 요인에 대한 규명, 불확도를 편리하게 산정할 수 있는 툴을 개발하고자 하였다. 불확도 산정 표준안으로 최근 WMO를 위시한 국제적으로 하천 유량 측정 불확도 표준안으로 채택되고 있는 GUM(Guide to the Expression of Uncertainty Measurement)을 기반으로 이동식 ADCP 유량 산정 알고리즘을 적용하여 불확도 적용 기법을 개발하였다. GUM 표준안을 기반으로 유량 측정불확도를 산정하기 위한 불확도 요인분석은 실규모 하천의 특성을 대부분 모의할 수 있는 한국건설기술연구원의 안동하천실험센터에서 수행된 실험자료를 기반으로 다양한 인자들에 대한 요소 별 불확도 분석을 수행하였다. GUM 표준안에 의하면 불확도 요인들은 오차전파의 법칙에 기반하여 전체 불확도에 전파되며, 이렇게 합성된 불확도는 t-분포의 신뢰수준 95%일 경우의 보정계수 2를 곱하여 최종적으로 확장불확도를 산정하게 된다. 이동측정방식의 ADCP의 경우 GUM 표준안에 적용하여 불확도를 평가하기 위해서 사용되는 수식이 방대하고, 매우 복잡하기 때문에 이를 실무자가 평가하기에는 한계가 있다. 이에 따라 본 연구에서는 ADCP의 유량 측정불확도를 보다 편리하게 평가하기 위하여 ADCP 유량 측정불확도 평가 소프트웨어인 AQUA(ADCP Discharge Uncertainty Assesment)를 개발하였으며, 이를 통해 실무자나 연구자들이 ADCP의 불확도 평가에 보다 편리하게 접근할 수 있을 것이라 판단된다.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.10 no.5
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• pp.409-416
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• 2017

In this paper, we consider a framework of compressed sensing over finite fields. One measurement sample is obtained by an inner product of a row of a sensing matrix and a sparse signal vector. A recovery algorithm proposed in this study for sparse signals based probabilistic decoding is used to find a solution of compressed sensing. Until now compressed sensing theory has dealt with real-valued or complex-valued systems, but for the processing of the original real or complex signals, the loss of the information occurs from the discretization. The motivation of this work can be found in efforts to solve inverse problems for discrete signals. The framework proposed in this paper uses a parity-check matrix of low-density parity-check (LDPC) codes developed in coding theory as a sensing matrix. We develop a stochastic algorithm to reconstruct sparse signals over finite field. Unlike LDPC decoding, which is published in existing coding theory, we design an iterative algorithm using probability distribution of sparse signals. Through the proposed recovery algorithm, we achieve better reconstruction performance as the size of finite fields increases. Since the sensing matrix of compressed sensing shows good performance even in the low density matrix such as the parity-check matrix, it is expected to be actively used in applications considering discrete signals.

• Journal of the Korea Computer Graphics Society
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• v.8 no.2
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• pp.1-7
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• 2002

The fast extraction of the silhouettes of a model is very useful for many applications in computer graphics and animation. In this paper, we present an efficient algorithm to compute a sequence of perspective silhouettes for a polyhedral model from a moving viewpoint. The viewpoint is assumed to move along a trajectory q(t), which is a space curve of a time parameter t. Then, we can compute the time-intervals for each edge of the model to be contained in the silhouette by two major computations: (i) intersecting q(t) with two planes and (ii) a number of dot products. If q(t) is a curve of degree n, then there are at most of n + 1 time-intervals for an edge to be in a silhouette. For each time point $t_i$ we can extract silhouette edges by searching the intervals containing $t_i$ among the computed intervals. For the efficient search, we propose two kinds of data structures for storing the intervals: an interval tree and an array. Our algorithm can be easily extended to compute the parallel silhouettes with minor modifications.