• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.2
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• pp.163-173
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• 2013

We present a new computer vision technique which can detect unexpected or static vertical objects in road driving environment. We first obtain temporal and spatial difference images in each frame of a stereo video sequence. Using the difference images, we then generate VO and HO maps by improving the conventional V and H disparity maps. From the VO and HO maps, candidate areas of vertical obstacles on the road are detected. Finally, the candidate areas are merged and refined to detect vertical obstacles.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.34S no.10
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• pp.98-103
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• 1997

Given the small bit allocation for motion information in very low bit-rate coding, motion estimation using the block matching algorithm(BMA) fails to maintain an acceptable level of prediction errors. The reson is that the motion model, or spatial transformation, assumed in block matching cannot approximate the motion in the real world precisely with a small number of parameters. In order to overcome the drawback of the conventional block matching algorithm, several triangle-based methods which utilize triangular patches insead of blocks have been proposed. To estimate the motions of image sequences, these methods usually have been based on the combination of optical flow equation, affine transform, and iteration. But the compuataional cost of these methods is expensive. This paper presents a fast motion estimation algorithm using a multiple linear regression model to solve the defects of the BMA and the triange-based methods. After describing the basic 2-D triangle-based method, the details of the proposed multiple linear regression model are presented along with the motion estimation results from one standard video sequence, representative of MPEG-4 class A data. The simulationresuls show that in the proposed method, the average PSNR is improved about 1.24 dB in comparison with the BMA method, and the computational cost is reduced about 25% in comparison with the 2-D triangle-based method.

• The Journal of Advanced Prosthodontics
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• v.9 no.6
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• pp.409-415
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• 2017

PURPOSE. Accurate information is essential in dentistry. The image information of missing teeth is used in optically based medical equipment in prosthodontic treatment. To evaluate oral scanners, the standardized model was examined from cases of image recognition errors of linear discriminant analysis (LDA), and a model that combines the variables with reference to ISO 12836:2015 was designed. MATERIALS AND METHODS. The basic model was fabricated by applying 4 factors to the tooth profile (chamfer, groove, curve, and square) and the bottom surface. Photo-type and video-type scanners were used to analyze 3D images after image capture. The scans were performed several times according to the prescribed sequence to distinguish the model from the one that did not form, and the results confirmed it to be the best. RESULTS. In the case of the initial basic model, a 3D shape could not be obtained by scanning even if several shots were taken. Subsequently, the recognition rate of the image was improved with every variable factor, and the difference depends on the tooth profile and the pattern of the floor surface. CONCLUSION. Based on the recognition error of the LDA, the recognition rate decreases when the model has a similar pattern. Therefore, to obtain the accurate 3D data, the difference of each class needs to be provided when developing a standardized model.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.38 no.6
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• pp.712-720
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• 2001

In this paper, we propose an efficient method to detect abrupt shot changes in a video sequence using an unsupervised clustering. Conventional clustering-based shot change detection algorithms use multiple features in order to overcome the shortcomings of a single feature. In such methods it is very important to determine the appropriate initial cluster centers well. In this paper we propose a modified k-means clustering algorithm which estimates the initial cluster center adaptively. Experimental results show that the proposed algorithm works well.

• Annual Conference of KIPS
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• 2001.04b
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• pp.879-882
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• 2001

장면 전환 검출을 위한 기존의 주요 방법은 대부분 화소값 차이, 통계적 차이, 그리고 일반적으로 가장 많이 사용하는 히스토그램 비교법등이었다. 이러한 방법에서는 각 비디오 프레임내에 포함되어 있는 영상의 내용 변화에 의한 장면 전환을 검출하기가 어렵고 히스토그램이 비슷한 경우 장면 전환 검출을 할 수 없었다. 본 논문에서는 비디오 시퀀스로부터 빠른 움직임을 포함하는 장면의 변화를 검출하는 객체의 중심점을 이용한 영역분할기법을 제안하였다. 제안하는 방법은 두 개의 프레임간 차영상을 이용해서 명암차를 추출한 후 화소값과 객체 영역의 중심점을 구한 후 사등분 분할하여 영역객체의 평균 및 분산값을 이용해서 내용에 의한 장면 전환도 검출하였다. 실험결과 제안된 방법에 의한 장면 전환 검출은 기존의 다른 방법에 비해 더 나은 성능을 얻었다.

• Smart Structures and Systems
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• v.6 no.9
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• pp.1025-1039
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• 2010

Measuring displacement response for civil structures is very important for assessing their performance, safety and integrity. Recently, video-based techniques that utilize low-cost high-resolution digital cameras have been developed for such an application. These techniques however have relatively low sampling frequency and the results are usually contaminated with noises. In this study, an integrated visual-inertial measurement method that combines a monocular videogrammetric displacement measurement technique and a collocated accelerometer is proposed for displacement and velocity measurement of civil engineering structures. The monocular videogrammetric technique extracts three-dimensional translation and rotation of a planar target from an image sequence recorded by one camera. The obtained displacement is then fused with acceleration measured from a collocated accelerometer using a multi-rate Kalman filter with smoothing technique. This data fusion not only can improve the accuracy and the frequency bandwidth of displacement measurement but also provide estimate for velocity. The proposed measurement technique is illustrated by a shake table test and a pedestrian bridge test. Results show that the fusion of displacement and acceleration can mitigate their respective limitations and produce more accurate displacement and velocity responses with a broader frequency bandwidth.

• IEMEK Journal of Embedded Systems and Applications
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• v.9 no.3
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• pp.145-150
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• 2014

This paper presents an effective vision based method for LED traffic light detection at the daytime. First, the proposed method calculates horizontal coordinates to set region of interest (ROI) on input sequence images. Second, the proposed uses color segmentation method to extract region of green and red traffic light. Next, to classify traffic light and another noise, shape filter and haar-like feature value are used. Finally, temporal delay filter with weight is applied to remove blinking effect of LED traffic light, and state and weight of traffic light detection are used to classify types of traffic light. For simulations, the proposed method is implemented through Intel Core CPU with 2.80 GHz and 4 GB RAM, and tested on the urban and rural road video. Average detection rate of traffic light is 94.50 % and average recognition rate of traffic type is 90.24 %. Average computing time of the proposed method is 11 ms.

• The Journal of the Korea institute of electronic communication sciences
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• v.5 no.5
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• pp.459-464
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• 2010

Computer programs are required from all areas in society including machine, space, aviation, and medicine. However, the programming curriculum is getting hard despite a lot of teaching materials and video lessons. Programming languages are very diverse, but most of them use the same structure, and they only have different expression methods. Therefore, if one learns one programming language, then it doesn't need to spend a lot of time and efforts to learn another programming langue. Most programming languages use the structure of sequence, selection, and repletion in general. The important thing for programming learners is the structure or algorithm of programming not the grammar of program. This study designed and implemented the language learning system to learn structured programming by using a flowchart.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2002.11a
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• pp.163-166
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• 2002

OFDM should be used for the fourth generation communication for high speed communication. Because of high spectral efficiency and high tolerance to fading channel, OFDM is applied to many high speed wire and wirless communication such as DAB(Digital Audio Broudcast), DVB(Digital Video Broadcast), IMT 2000 etc. Inter-modulation, however, is derived from PAR(Peak to Average Power Ratio) of OFDM signals. The paper describes PTS(Partial Transmit Sequence) and SLM(Select Mapping) of an existing methods which can reduce PAR. And then the document introduces the new method that is called "Combine PAR method". The method proposed in this paper is to combine PTS and SLM. As a result of the simulation, Combine PAR method is better than the existing methods.g methods.

• Journal of the Semiconductor & Display Technology
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• v.10 no.2
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• pp.31-38
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• 2011

This paper introduces a video based traffic monitoring system for detecting vehicles and obstacles on the road. To segment moving objects from image sequence, we adopt the background subtraction algorithm based on the local binary patterns (LBP). Recently, LBP based texture analysis techniques are becoming popular tools for various machine vision applications such as face recognition, object classification and so on. In this paper, we adopt an extension of LBP, called the Diagonal LBP (DLBP), to handle the background subtraction problem arise in vision-based autonomous parking systems. It reduces the code length of LBP by half and improves the computation complexity drastically. An edge based shadow removal and blob merging procedure are also applied to the foreground blobs, and a pose estimation technique is utilized for calculating the position and heading angle of the moving object precisely. Experimental results revealed that our system works well for real-time vehicle localization and tracking applications.