• Journal of KIISE:Computing Practices and Letters
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• v.14 no.6
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• pp.619-623
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• 2008

A lane detection system is one of the major components of intelligent vehicle systems. Difficulties in lane detection mainly come from not only various weather conditions but also a variety of special environment. This paper describes a simple and stable method for the broken lane tracking in various environments. Probabilistic Hough Transform (PHT) and the Least-square method (LSM) are used to track and correct the lane orientation. For the efficiency of the proposed method, two regions of interest (ROIs) are placed in the lower part of each image, where lane marking areas usually appear with less intervention in our system view. By testing in both a set of static images and video sequences, the experiments showed that the proposed approach yielded robust and reliable results.

• Journal of KIISE:Computing Practices and Letters
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• v.14 no.6
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• pp.547-558
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• 2008

Embedded system is tightly coupled with heterogeneous layers such as application, as kernel, device driver, HAL and hardware. Embedded system is customized for the specific purpose and hardware. In addition, the product cycle is so fast that software and hardware, which are developed by several vendors, are integrated together under unstable status. Therefore, there are lots of possibilities of faults in all layers. Because embedded software developers test their codes integrated with faulty layers, they cannot confirm 'whether testing of every aspects was completed, their code was failed, or integrated software/hardware has some problems'. In this paper, we propose an embedded software interface test method and a test tool called Justitia for detecting faults and tracing causes in the interface among heterogeneous layers. The proposed technique is an automated method which improves debugging upto professional testing using an emulator for helping developer.

• Journal of Korea Multimedia Society
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• v.10 no.8
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• pp.981-996
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• 2007

In this paper, we describe a method that can recognize gestures by obtaining motion features information with principal factor analysis from sequential gesture images. In the algorithm, firstly, a two dimensional silhouette region including human gesture is segmented and then geometric features are extracted from it. Here, global features information which is selected as some meaningful key feature effectively expressing gestures with principal factor analysis is used. Obtained motion history information representing time variation of gestures from extracted feature construct one gesture subspace. Finally, projected model feature value into the gesture space is transformed as specific state symbols by grouping algorithm to be use as input symbols of HMM and input gesture is recognized as one of the model gesture with high probability. Proposed method has achieved higher recognition rate than others using only shape information of human body as in an appearance-based method or extracting features intuitively from complicated gestures, because this algorithm constructs gesture models with feature factors that have high contribution rate using principal factor analysis.

• Journal of Intelligence and Information Systems
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• v.15 no.3
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• pp.53-65
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• 2009

The part-of-speech determination is necessary for resolving the part-of-speech ambiguity in English-Korean machine translation. The part-of-speech ambiguity causes high parsing complexity and makes the accurate translation difficult. In order to solve the problem, the resolution of the part-of-speech ambiguity must be performed after the lexical analysis and before the parsing. This paper proposes the CatAmRes model, which resolves the part-of-speech ambiguity, and compares the performance with that of other part-of-speech tagging methods. CatAmRes model determines the part-of-speech using the probability distribution from Bayesian network training and the statistical information, which are based on the Penn Treebank corpus. The proposed CatAmRes model consists of Calculator and POSDeterminer. Calculator calculates the degree of appropriateness of the partof-speech, and POSDeterminer determines the part-of-speech of the word based on the calculated values. In the experiment, we measure the performance using sentences from WSJ, Brown, IBM corpus.

• Proceedings of the Korea Technology Innovation Society Conference
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• 2017.05a
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• pp.161-174
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• 2017

최근 들어 기술벤처기업에 대한 투자가 증가하고, 이를 위한 기술신용평가의 역할이 증대하였다. 그러나 금융권에서 바라보는 기술신용평가의 경우, 해당 기업의 신용등급이나 기술(력) 등급평가에 초점을 두어, 대상기술의 사업화 및 수익성 관점을 체계적으로 반영하지 못하는 한계를 지닌다. 따라서, 벤처캐피털(VC)이나 엔젤투자자를 비롯한 금융권에서 대상기술의 수익성 정보를 참조하거나 기술벤처기업 설립시 기술지분을 참고하는 등, 기존 기술이전거래 협상참조용이나 담보 보증용에 널리 이용되던 기술가치평가의 활용범위가 급격히 확대되고 있다. 제조 서비스 분야의 일반 기술 뿐만이 아니라, 바이오 제약 의료 분야 기술에서도 미래 투입되어야 하는 사업화 소요기간 및 비용을 고려하여 기술가치를 산정해야 할 때가 있다. 기존의 현금흐름할인법(DCF법)이 연속된 투자에 대한 고려를 못하거나 기술적용 제품의 상용화 투입비용에 대한 확률적인 속성을 반영하지 못하는 등 한계점을 지니고 있다. 그러나 기술과 투자의 가치는 기회가치로 보고 자원배분을 위한 의사결정 정보를 감안해야 하므로, 실물옵션의 개념을 적용하는 것이 바람직하다고 여겨진다. 흔히 기업가치를 평가할 때 주가의 변동성(volatility) 개념을 도입하여 전일종가 대비 익일시가의 분산값을 활용하기도 한다. 이러한 개념을 기술가치평가에 적용하기 위해서는 '주가의 연속성(상대적 미세한 변화)' 및 '양(+)의 조건'을 고려해야 하는데, 실제 기술가치평가 상의 현금흐름은 사업초기년도 음(-)의 값이 나타나거나 2~3년 내외의 짧은 수익예상기간 하에서는 주가와 같은 변동성을 도출하는데 무리가 있다. 따라서 많은 문헌에서 연구된 바와 같이, 실물옵션 기반의 기술가치 산정을 위한 블랙-숄즈 모형에서 변동성과 기초자산가치, 그리고 사업화비용 간의 관계를 살펴볼 필요가 있다. 아울러 옵션가격결정모형(Option Pricing Model)에서 불확실성을 반영한 기초자산의 현재가치와 사업화비용의 현재가치분이 특정 임계조건 하에서 '옵션행사 포기(NAT; no action taken)' 영역으로 구분되는 지를 수학적으로 도출하고 관찰변수(입력값)에 따른 옵션가치 산출표를 개발하여 제시한다.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39C no.12
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• pp.1346-1351
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• 2014

We propose a novel approach for stereophonic acoustic echo suppression using spectro-temporal filtering based on soft decision. Unlike the conventional approaches estimating the echo pathes directly, the proposed technique can estimate stereo echo spectra without any double-talk detector. In order to improve the estimation of echo spectra, the extended power spectrum density matrix and echo overestimation control matrix are applied on this method. In addition, this echo suppression technique is based on soft decision technique using speech absence probability in STFT domain. Experimental results show that the proposed method improves compared with the conventional approaches.

• The Korean Journal of Applied Statistics
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• v.19 no.1
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• pp.97-110
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• 2006

Since it is well-established that even high quality data tend to contain outliers, one would expect fat? greater reliance on robust regression techniques than is actually observed. But most of all robust regression estimators suffers from the computational difficulties and the lower efficiency than the least squares under the normal error model. The weighted self-tuning estimator (WSTE) recently suggested by Lee (2004) has no more computational difficulty and it has the asymptotic normality and the high break-down point simultaneously. Although it has better properties than the other robust estimators, WSTE does not have full efficiency under the normal error model through the weighted least squares which is widely used. This paper introduces a new approach as called the reweighted WSTE (RWSTE), whose scale estimator is adaptively estimated by the self-tuning constant. A Monte Carlo study shows that new approach has better behavior than the general weighted least squares method under the normal model and the large data.

• Journal of Digital Convergence
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• v.12 no.7
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• pp.239-245
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• 2014

In this paper, a weighted value wrinkle detection method is suggested based on the analysis on the entire facial features such as face contour, face size, eyes and ears. Firstly, the main facial elements are detected with AAM method entirely from the input screen images. Such elements are mainly composed of shape-based and appearance methods. These are used for learning the facial model and for matching the face from new screen images based on the learned models. Secondly, the face and background are separated in the screen image. Four points with the biggest possibilities for wrinkling are selected from the face and high wrinkle weighted values are assigned to them. Finally, the wrinkles are detected by applying Canny edge algorithm for the interested points of weighted value. The suggested algorithm adopts various screen images for experiment. The experiments display the excellent results of face and wrinkle detection in the most of the screen images.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.1
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• pp.9-14
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• 2013

In this paper, we propose a low complexity bilateral search SIC for OFDM in fast time-varying channels. Due to the possibility of error propagation in SIC, symbol detection ordering within the block of symbols has a significant effect on the overall performance. In this paper, the first symbol to be detected is determined based on CSEP values, and then the next symbol to be detected is selected according to the updated CSEP while bilaterally searching from the boundary of the detected symbol group. Through computer simulations, we show that the proposed method has performance improvements with almost the same computation complexity over the conventional methods in the high SNR region. It has a performance approaching the MFB, known as the performance upper bound, within 2dB at the BER of $10^{-5}$.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.10
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• pp.2121-2128
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• 2012

This paper proposed the real time face area detection using Wavelet transform and the strong detection algorithm that satisfies the efficiency of computation and detection performance at the same time was proposed. The detected face image recognizes the face by configuring the low-dimensional face symbol through the principal component analysis. The proposed method is well suited for real-time system construction because it doesn't require a lot of computation compared to the existing geometric feature-based method or appearance-based method and it can maintain high recognition rate using the minimum amount of information. In addition, in order to reduce the wrong recognition or recognition error occurred during face recognition, the input symbol of Hidden Markov Model is used by configuring the feature values projected to the unique space as a certain symbol through clustering algorithm. By doing so, any input face will be recognized as a face model that has the highest probability. As a result of experiment, when comparing the existing method Euclidean and Mahananobis, the proposed method showed superior recognition performance in incorrect matching or matching error.