• 디지털융복합연구
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• 제10권3호
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• pp.173-178
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• 2012

본 논문에서는 영상의 관심 영역을 선택추출하여 효과적으로 객체를 추출 할 수 있는 관심 영역 지도(Saliency Map) 생성 기법을 제안하였다. 제안하는 방법은 객체의 윤곽선에 초점을 맞추어 단일영상의 에지(Edge), HSV 색상 모델의 H(Hue)성분, 포커스(Focus), 엔트로피(Entropy)의 네 가지 특징 정보를 이용한 각각의 특징 지도(Feature Map)를 생성하고, 생성된 특징 지도들을 중심 주변 차이(Center Surround Differences)를 이용하여 중요도 지도(conspicuity map)를 생성하게 된다. 이후 생성된 중요도 지도들을 조합함으로써 관심 영역 지도를 생성하게 된다. 제안한 기법을 이용하여 생성한 관심 영역 지도를 기존 기법의 관심 영역 지도와 비교한 결과 제안한 기법의 우수함을 알 수 있었다.

• 대한안전경영과학회지
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• 제6권2호
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• pp.177-186
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• 2004

Decision analysis has becomes an important technique for decision making in the face of uncertainty. It is characterized by enumerating all the available courses of action, identifying the payoffs for all possible outcomes, and quantifying the subjective probabilities for the all possible random events. When the data are available, decision analysis becomes a powerful tool for determining an optimal course of action. We study the multi-attribute decision making in a compensatory models. In this paper, we use the entropy methods in weights calculating. For the purpose of making optimal decision, the data of five different car models are used. For computing, we used Visual Numerica Version 1.0 software package.

• Journal of Communications and Networks
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• 제10권1호
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• pp.89-97
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• 2008

Anomaly detection systems playa significant role in protection mechanism against attacks launched on a network. The greatest challenge in designing systems detecting anomalous exploits is defining what to measure. Effective yet simple, Shannon entropy metrics have been successfully used to detect specific types of malicious traffic in a number of commercially available IDS's. We believe that Renyi entropy measures can also adequately describe the characteristics of a network as a whole as well as detect abnormal traces in the observed traffic. In addition, Renyi entropy metrics might boost sensitivity of the methods when disambiguating certain anomalous patterns. In this paper we describe our efforts to understand how Renyi mutual information can be applied to anomaly detection as an offline computation. An initial analysis has been performed to determine how well fast spreading worms (Slammer, Code Red, and Welchia) can be detected using our technique. We use both synthetic and real data audits to illustrate the potentials of our method and provide a tentative explanation of the results.

• 반도체디스플레이기술학회지
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• 제20권3호
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• pp.93-96
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• 2021

The desire for a technology that can mechanically acquire 2D images starting with the manual method of drawing has been making possible a wide range of modern image-based technologies and applications over a period. Moreover, this trend of the utilization of image-related technology as well as image-based information is likely to continue. Naturally, as like other technology areas, the function that humans produce and utilize by using images needs to be automated by using computing-based technologies. Surprisingly, technology using images in the future will be able to discover knowledge that humans have never known before through the information-related process that enables new perception, far beyond the scope of use that human has used before. Regarding this trend, the manipulation and configuration of massively distributed image database system is strongly demanded. In this paper, we discuss image identifier production methods based on the utilization of the image hashing technique which especially puts emphasis over an entropy operator.

• 한국통신학회논문지
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• 제9권3호
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• pp.103-107
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• 1984

데이터 통신의 급격한 발전으로 인하여 각종 정보를 손쉽게 이용할 수 있게 되었다. 이같이 얻은 정보들을 송수신함에 있어서 가능한 한 비트수를 최소화하여 정보를 전송하는 것이 필요로 하게 되었다. 즉 8개의 symbol을 다룬 경우의 entropy가 평균적으로 3.5bytes로서 다른 방식에서 사용된 것보다 적어도 1byte이상 축약되는 OCM(Octal-Compact Mapping)방식을 제시함과 이같이 최소화로 인해 redundancy가 상당히 감소되며 동시에 기존에 사용한 data compression 방식보다 효율성이 좋은 방식을 본 논문에서 제시하였다.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2002년도 ITC-CSCC -2
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• pp.908-911
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• 2002

Over the past 30 years, many efficient 2D video coding techniques have been presented and developed from many research centers for commercialization. However, direct application of these monocular compression schemes is not optimal for stereo video coding. In this paper, we present a new technique for coding stereo video sequences based on Discrete Wavelet Transform (DWT). The proposed technique exploits Zerotree Entropy Coding (ZTE) that makes use of the wavelet block concept to achieve low bit rate stereo video coding. The one of two image streams, called main stream, is independently coded by modified MPEG-4 encoder and the other stream, called auxiliary stream, is coded by predicting from its corresponding image, its previous image or its follow image.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2005년도 ICCAS
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• pp.2485-2489
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• 2005

This paper introduces a new preprocessing scheme to replace original data of gray scale images with particular ordered data so that performance of lossless compression can be improved more efficiently. As a kind of preprocessing technique to maximize performance of entropy encoder, the proposed method converts the input image data into more compressible form. Before encoding a stream of the input image, the proposed preprocessor counts co-occurrence frequencies for neighboring pixel pairs. Then, it replaces each pair of adjacent gray values with particular ordered numbers based on the investigated co-occurrence frequencies. When compressing ordered image using entropy encoder, we can expect to raise compression rate more highly because of enhanced statistical feature of the input image. In this paper, we show that lossless compression rate increased by up to 37.85% when comparing results from compressing preprocessed and non-preprocessed image data using entropy encoder such as Huffman, Arithmetic encoder.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2008년도 춘계학술대회 논문집
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• pp.158-163
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• 2008

In inverse synthetic aperture radar (ISAR) imaging, An ISAR autofocusing algorithm is essential to obtain well-focused ISAR images. Traditional methods have relied on the approximation that the phase error due to target motion is a function of the cross-range dimension only. However, in the stepped-frequency radar system, it tends to become a two-dimensional function of both down-range and cross-range, especially when target's movement is very fast and the pulse repetition frequency (PRF) is low. In order to remove the phase error along down-range, this paper proposes a method called SAEM (subarray averaging and entropy minimization) [1] that uses a subarray averaging concept in conjunction with the entropy cost function in order to find target motion parameters, and a novel 2-D optimization technique with the inherent properties of the proposed entropy-based cost function. A well-focused ISAR image can be obtained from the combination of the proposed method and a traditional autofocus algorithm that removes the phase error along the cross-range dimension. The effectiveness of this method is illustrated and analyzed with simulated targets comprised of point scatters.

• 한국자동차공학회논문집
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• 제12권1호
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• pp.39-47
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• 2004

The objective of this study is to analyse the spray characteristics according to the injection duration under ambient pressure condition and to investigate the relationship between vorticity and entropy for controlling diffusion process that is the most important thing during the intake stroke injection process. Therefore, the spray velocity was obtained by using the PIV method that has been an useful optical diagnostics technology, and vorticity calculated from spray velocity component with vorticity algorithm. In addition, the homogeneous diffusion rate of spray was quantified by using the entropy analysis based on the Boltzmann's statistical thermodynamics. From these method, we found that as injection duration increases, spray velocity increases and the location of vortex is moved to the downstream of spray. In the same condition, as the entropy decrease, mean vorticity increases. This means that the concentration of spray droplets caused by the increase of injection duration is more effective than the increase of momentum dissipation.

• Journal of Information Processing Systems
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• 제15권2호
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• pp.288-304
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• 2019

The growth of telemedicine-based wireless communication for images-magnetic resonance imaging (MRI) and computed tomography (CT)-leads to the necessity of learning the concept of image compression. Over the years, the transform based and spatial based compression techniques have attracted many types of researches and achieve better results at the cost of high computational complexity. In order to overcome this, the optimization techniques are considered with the existing image compression techniques. However, it fails to preserve the original content of the diagnostic information and cause artifacts at high compression ratio. In this paper, the concept of histogram based multilevel thresholding (HMT) using entropy is appended with the optimization algorithm to compress the medical images effectively. However, the method becomes time consuming during the measurement of the randomness from the image pixel group and not suitable for medical applications. Hence, an attempt has been made in this paper to develop an HMT based image compression by utilizing the opposition based improved harmony search algorithm (OIHSA) as an optimization technique along with the entropy. Further, the enhancement of the significant information present in the medical images are improved by the proper selection of entropy and the number of thresholds chosen to reconstruct the compressed image.