• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.403-403
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• 2000

Generally estimation of driving direction uses the way which uses lane detection and vanishing point in autonomous-driving system. Especially we use Sub-window for decreasing Process time when we detect lane, but fixed sub-window can not detect lane because of some factors in road image. So we suggest algorithm using one-dimension line scan method to detect an exact position of lane.

• Journal of the Korean Data and Information Science Society
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• v.18 no.3
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• pp.669-678
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• 2007

An algorithm to detect the number of discontinuity points of the variance function in regression model is proposed. The proposed algorithm is based on the left and right one-sided kernel estimators of the second moment function and test statistics of the existence of a discontinuity point coming from the asymptotic distribution of the estimated jump size. The finite sample performance is illustrated by simulated example.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.25 no.6
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• pp.1465-1475
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• 2015

Cheating detection models in the online games can be divided into two parts. The one is on client based model, which is designed to detect malicious programs not to be run while playing the games. The other one is server based model, which distinguishes the difference between benign users and cheaters by the server log analysis. The client based model provides various features to prevent games from cheating, For instance, Anti-reversing, memory manipulation and so on. However, being deployed and operated on the client side is a huge weak point as cheaters can analyze and bypass the detection features. That Is why the server based model is an emerging way to detect cheating users in online games. But the simple log data such as FPS's one can be hard to find validate difference between two of them. In this paper, In order to compensate for the disadvantages of the two detection model above, We use the existing game security solution log as well as the server one to bring high performance as well as detection ratio compared to the existing detection models in the market.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.62 no.4
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• pp.562-565
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• 2013

A new variable rate speech coding technique is proposed. The method is based on the observation that the speech signal approximately looks linear for a very short period of time. The information transmitted is the location and data value of inflection points. If the distance between the inflection points is large, the mid point location and its data value are also delivered. Thus, the encoder transmits both the location and the data value for the inflection samples, but the location only for the non-inflection points. The location information is expressed using one bit for each sample, 0 for non-inflection and 1 for inflection point. At the receiver, using the interpolation, the decoder estimates the untransmitted sample values for non-inflection locations from the received sample values for the inflection samples. With 50 % of computational cost of the existing CVSD delta modulation, the proposed method is expected to achieve the data rate of 36 to 38 kbps and the SNR of 10 to 13 dB.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.25 no.5
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• pp.841-849
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• 2001

The pixel information of the object was obtained sequentially and pixels were clustered to a label by the line labeling method. Feature points were determined by finding the slope for edge pixels after selecting the fixed number of edge pixels. The slope was estimated by the least square method to reduce the detection error. Once a matching point was determined by comparing the feature information of the object and the pattern, the parameters for translation, scaling and rotation were obtained by selecting the longer line of the two which passed through the matching point from left and right sides. Finally, modified Hausdorff Distance has been used to identify the similarity between the object and the given pattern. The multi-label method was developed for recognizing the patterns with more than one label, which performs the modified Hausdorff Distance twice. Experiments have been performed to verify the performance of the proposed algorithm and method for simple target image, complex target image, simple pattern, and complex pattern as well as the partially hidden object. It was proved via experiments that the proposed image matching algorithm for recognizing the object had a good performance of matching.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.30 no.6_2
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• pp.643-651
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• 2012

Object recognition belongs to high-level processing that is one of the difficult and challenging tasks in computer vision. Digital photogrammetry based on the computer vision paradigm has begun to emerge in the middle of 1980s. However, the ultimate goal of digital photogrammetry - intelligent and autonomous processing of surface reconstruction - is not achieved yet. Object recognition requires a robust shape description about objects. However, most of the shape descriptors aim to apply 2D space for image data. Therefore, such descriptors have to be extended to deal with 3D data such as LiDAR(Light Detection and Ranging) data obtained from ALS(Airborne Laser Scanner) system. This paper introduces extension of chain code to 3D object space with hierarchical approach for segmenting point cloud data. The experiment demonstrates effectiveness and robustness of the proposed method for shape description and point cloud data segmentation. Geometric characteristics of various roof types are well described that will be eventually base for the object modeling. Segmentation accuracy of the simulated data was evaluated by measuring coordinates of the corners on the segmented patch boundaries. The overall RMSE(Root Mean Square Error) is equivalent to the average distance between points, i.e., GSD(Ground Sampling Distance).

• Journal of Information Processing Systems
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• v.2 no.1
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• pp.52-57
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• 2006

One of the important functions of an Intelligent Transportation System (ITS) is to classify vehicle types using a vision system. We propose a method using machine-learning algorithms for this classification problem with 3-D object model fitting. It is also necessary to detect road lanes from a fixed traffic surveillance camera in preparation for model fitting. We apply a background mask and line analysis algorithm based on statistical measures to Hough Transform (HT) in order to remove noise and false positive road lanes. The results show that this method is quite efficient in terms of quality.

• Proceedings of the IEEK Conference
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• 2000.11a
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• pp.505-508
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• 2000

The success of target reconstruction in SAR(Synthetic Aperture Radar) imaging system is greatly dependent on the coherent detection. Primary causes of incoherent detection are uncompensated target or sensor motion, random turbulence in propagation media, wrong path in radar platform, and etc. And these appear as multiplicative phase error to the echoed signal, which consequently, causes fatal degradations such as fading or dislocation of target image. In this paper, we present iterative phase error estimation scheme which uses echoed data in all temporal frequencies. We started with analyzing wave equation for one point target and extend to overall echoed data from the target scene - The two wave equations governing the SAR signal at two temporal frequencies of the radar signal are combined to derive a method to reconstruct the complex phase error function. Eventually, this operation attains phase error correction algorithm from the total received SAR signal. We verify the success of the proposed algorithm by applying it to the simulated spotlight-mode SAR data.

• Proceedings of the Acoustical Society of Korea Conference
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• autumn
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• pp.97-100
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• 1999

본 논문은 자동차의 편의성 및 안전성의 동시 확보를 위하여, 보조적 스위치의 조작없이 상시 음성의 입$\cdot$출력이 가능하도록 하였고, 남성과 여성을 구별하기 위하여 피치검출법을 사용하여 속도별로 구분하였다. 또한, band pass filter를 이용하여 자동으로 잡음하에서 정확하게 음성추간 검출(End Point Detection)을 하게 하였다. Reference Pattern은 DMS(Dynaminc Multi-Section)[1]모델을 사용하려고, 음성의 특징 파라미터와 인식 알고리즘은 PLP 13차와 One Stage Dynamic Programming(OSDP)를 사용하였다. 시내주행중인 자동차 환경에서 자주 사용되는 차량제어 명령어 30단어를 가지고 실험한 결과 40-80km에서 화자독립 남성 $96\%$, 여성 $94.4\%$ 화자종속일 때 남성 $97\%$, 여성 $95\%$의 인식률을 얻을수 있었고 남성과 여성을 구분하므로 써 인식률을 향상 시켰다.

• IEMEK Journal of Embedded Systems and Applications
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• v.12 no.5
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• pp.277-286
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• 2017

This paper introduces mathematical modelling and control algorithm of expendable mine disposal vehicle. This vehicle has two longitudinal thrusters, one vertical thruster and internal mass moving system which can control pitch rate. Also, the vehicle has an optical camera and forward looking sonar for underwater mine detection and classification. The vehicle is controlled via an optical cable connected with operating console on the mother ship. We describe the vehicle's 6DOF dynamic model and controller which can track the desired trajectory for the way-point tracking. These simulation results shows guidance and maneuvering performance which has other sensor data or not.