• Title/Summary/Keyword: Point pattern matching

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Developing Head/Eye Tracking System and Sync Verification (헤드/아이 통합 트랙커 개발 및 통합 성능 검증)

  • Kim, Jeong-Ho;Lee, Dae-Woo;Heo, Se-Jong;Park, Chan-Gook;Baek, Kwang-Yul;Bang, Hyo-Choong
    • Journal of Institute of Control, Robotics and Systems
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    • v.16 no.1
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    • pp.90-95
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    • 2010
  • This paper describes the development of integrated head and eye tracker system. Vision based head tracker is performed and it has 7mm error in 300mm translation. The epi-polar method and point matching are used for determining a position of head and rotational degree. High brightness LEDs are installed on helmet and the installed pattern is very important to match the points of stereo system. Eye tracker also uses LED for constant illumination. A Position of gazed object(3m distance) is determined by pupil tracking and eye tracker has 1~5 pixel error. Integration of result data of each tracking system is important. RS-232C communication is applied to integrated system and triggering signal is used for synchronization.

A Method for Measurement of Limiting Intrinsic Non-Uniformity Due to Process in CCD-Multiplexers for Focal Plane Arrays

  • Bhan, R.K.;Saxena, R.S.
    • JSTS:Journal of Semiconductor Technology and Science
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    • v.2 no.1
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    • pp.87-92
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    • 2002
  • We present a simple experimental method for determination of limiting intrinsic fixed-pattern non-uniformity (NU) due to fabrication process in two-dimensional CCD multiplexers (MUXs) that are used for hybrid focal plane arrays. Here, this is done by determining separately the two NUs viz. that are $V_T$ dependent and $V_T$ independent. From these measurements, process dependent NU can be extracted. It is argued that $V_T$ dependent NU can be eliminated by designing novel input circuits whereas $V_T$ independent NU, primarily, dependent on process control and material variations may be reduced but cannot be eliminated completely and hence limits the FPA performance eventually.

Study on Design of Fingerprint Recognition Embedded System using Neural Network

  • Kim, Dong Han;Kim, Jung Hoon;Lee, Sang Hae
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.4 no.3
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    • pp.347-352
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    • 2004
  • We generated blocks from the direction-extracted fingerprint during the pre-process of the fingerprint recognition algorithm and performed training by using the direction minutiae of each block as the input pattern of the neural network, so that we extracted the core points to use in the matching. Based on this, we designed the fingerprint recognition embedded system and tested it by using the control board and the serial communication to utilize it for a variety of application systems. As a result, we can verify the reliance satisfactorily.

Automated System on Extracting Digital Pattern for TDGS Image Analysis (TDGS 영상 분석을 통한 자동적 디지털 패턴의 추출)

  • Chang, Hwan;Park, You-Na;Lee, Bog-Ju
    • Proceedings of the Korea Information Processing Society Conference
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    • 2003.05a
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    • pp.707-710
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    • 2003
  • 본 논문은 2차원 전기영동에 의해 나타나는 TOGS 영상을 분석하기 위한 시스템으로 실험적인 특성상 젤 위에 나타나는 반점들의 불규칙한 요소들이 많고 영상의 상태가 좋지 않은 경우 명암도가 떨어지는 반점들의 구분이 힘들게 된다. 기존의 전문가의 육안에 의한 TDGS 영상 분석은 그러한 불안적 요소들에 대해 유연하게 대처할 수 있는 능력이 있었다. 하지만, 그러한 예외적인 경우를 컴퓨터가 처리하기 위해서는 영상의 지역적 상태에 맞는 융통성 있는 영상처리 과정이 필요하고, 실제 분석에 사용되지 않는 반정들을 제외한 유효한 디지털 패턴의 판별이 요구된다. 이에 본 논문에서는 영상의 지역적 특성을 효과적으로 반영한 동적 이진화 방법을 통해 후보 패턴들을 추출하고, 모든 샘플들의 기준이 되는 Reference 패턴과 후보 패턴의 point matching 과정을 통해 디지털 패턴을 추출한다.

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Optimizing Shared Memory Accesses for GPGPU Computations (GPGPU를 위한 공유 메모리 최적화)

  • Tran, Nhat-Phuong;Lee, Myungho;Hong, Sugwon
    • Proceedings of the Korea Information Processing Society Conference
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    • 2012.11a
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    • pp.197-199
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    • 2012
  • Recently, a lot of general-purpose application programs in addition to graphic applications have been parallelized for boosting their performance using Graphic Processing Unit (GPU)'s excellent floating-point performance. In order to maximize the application performance on GPUs, optimizing the memory hierarchy and the on-chip caches such as the shared memory is essential. In this paper, we propose techniques to optimize the shared memory, and verify its effectiveness using a pattern matching application program.

A Prediction Search Algorithm by using Temporal and Spatial Motion Information from the Previous Frame (이전 프레임의 시공간 모션 정보에 의한 예측 탐색 알고리즘)

  • Kwak, Sung-Keun;Wee, Young-Cheul;Kimn, Ha-Jine
    • Journal of the Korea Computer Graphics Society
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    • v.9 no.3
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    • pp.23-29
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    • 2003
  • There is the temporal correlation of the video sequence between the motion vector of current block and the motion vector of the previous block. If we can obtain useful and enough information from the motion vector of the same coordinate block of the previous frame, the total number of search points used to find the motion vector of the current block may be reduced significantly. In this paper, we propose the block-matching motion estimation using an adaptive initial search point by the predicted motion information from the same block of the previous frame. And the first search point of the proposed algorithm is moved an initial point on the location of being possibility and the searching process after moving the first search point is processed according to the fast search pattern. Simulation results show that PSNR(Peak-to-Signal Noise Ratio) values are improved UP to the 1.05dB as depend on the image sequences and improved about 0.33~0.37dB on an average. Search times are reduced about 29~97% than the other fast search algorithms. Simulation results also show that the performance of the proposed scheme gives better subjective picture quality than the other fast search algorithms and is closer to that of the FS(Full Search) algorithm.

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New Fast Block-Matching Motion Estimation using Temporal and Spatial Correlation of Motion Vectors (움직임 벡터의 시공간 상관성을 이용한 새로운 고속 블럭 정합 움직임 추정 방식)

  • 남재열;서재수;곽진석;이명호;송근원
    • Journal of Broadcast Engineering
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    • v.5 no.2
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    • pp.247-259
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    • 2000
  • This paper introduces a new technique that reduces the search times and Improves the accuracy of motion estimation using high temporal and spatial correlation of motion vector. Instead of using the fixed first search Point of previously proposed search algorithms, the proposed method finds more accurate first search point as to compensating searching area using high temporal and spatial correlation of motion vector. Therefore, the main idea of proposed method is to find first search point to improve the performance of motion estimation and reduce the search times. The proposed method utilizes the direction of the same coordinate block of the previous frame compared with a block of the current frame to use temporal correlation and the direction of the adjacent blocks of the current frame to use spatial correlation. Based on these directions, we compute the first search point. We search the motion vector in the middle of computed first search point with two fixed search patterns. Using that idea, an efficient adaptive predicted direction search algorithm (APDSA) for block matching motion estimation is proposed. In the experimental results show that the PSNR values are improved up to the 3.6dB as depend on the Image sequences and advanced about 1.7dB on an average. The results of the comparison show that the performance of the proposed APDSA algorithm is better than those of other fast search algorithms whether the image sequence contains fast or slow motion, and is similar to the performance of the FS (Full Search) algorithm. Simulation results also show that the performance of the APDSA scheme gives better subjective picture quality than the other fast search algorithms and is closer to that of the FS algorithm.

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Fast Handwriting Recognition Using Model Graph (모델 그래프를 이용한 빠른 필기 인식 방법)

  • Oh, Se-Chang
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.16 no.5
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    • pp.892-898
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    • 2012
  • Rough classification methods are used to improving the recognition speed in many character recognition problems. In this case, some irreversible result can occur by an error in rough classification. Methods for duplicating each model in several classes are used in order to reduce this risk. But the errors by rough classfication can not be completely ruled out by these methods. In this paper, an recognition method is proposed to increase speed that matches models selectively without any increase in error. This method constructs a model graph using similarity between models. Then a search process begins from a particular point in the model graph. In this process, matching of unnecessary models are reduced that are not similar to the input pattern. In this paper, the proposed method is applied to the recognition problem of handwriting numbers and upper/lower cases of English alphabets. In the experiments, the proposed method was compared with the basic method that matches all models with input pattern. As a result, the same recognition rate, which has shown as the basic method, was obtained by controlling the out-degree of the model graph and the number of maintaining candidates during the search process thereby being increased the recognition speed to 2.45 times.

A Euclidean Reconstruction of 3D Face Data Using a One-Shot Absolutely Coded Pattern (단일 투사 절대 코드 패턴을 이용한 3차원 얼굴 데이터의 유클리디안 복원)

  • Kim, Byoung-Woo;Yu, Sun-Jin;Lee, Sang-Youn
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.42 no.6
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    • pp.133-140
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    • 2005
  • This paper presents a rapid face shape acquisition system. The system is composed of two cameras and one projector. The technique works by projecting a pattern on the object and capturing two images with two cameras. We use a 'one shot' system which provides 3D data acquired by single image per camera. The system is good for rapid data acquisition as our purpose. We use the 'absolutely coded pattern' using the hue and saturation of pattern lines. In this 'absolutely coded pattern' all patterns have absolute identification numbers. We solve the correspondence problem between the two images by using epipolar geometry and absolute identification numbers. In comparison to the 'relatively coded pattern' which uses relative identification numbers, the 'absolutely coded pattern' helps obtain rapid 3D data by one to one point matching on an epipolar line. Because we use two cameras, we obtain two images which have similar hue and saturation. This enables us to have the same absolute identification numbers in both images, and we can use the absolutely coded pattern for solving the correspondence problem. The proposed technique is applied to face data and the total time for shape acquisition is estimated.

The Design and Implementation of Anomaly Traffic Analysis System using Data Mining

  • Lee, Se-Yul;Cho, Sang-Yeop;Kim, Yong-Soo
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.8 no.4
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    • pp.316-321
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    • 2008
  • Advanced computer network technology enables computers to be connected in an open network environment. Despite the growing numbers of security threats to networks, most intrusion detection identifies security attacks mainly by detecting misuse using a set of rules based on past hacking patterns. This pattern matching has a high rate of false positives and can not detect new hacking patterns, which makes it vulnerable to previously unidentified attack patterns and variations in attack and increases false negatives. Intrusion detection and analysis technologies are thus required. This paper investigates the asymmetric costs of false errors to enhance the performances the detection systems. The proposed method utilizes the network model to consider the cost ratio of false errors. By comparing false positive errors with false negative errors, this scheme achieved better performance on the view point of both security and system performance objectives. The results of our empirical experiment show that the network model provides high accuracy in detection. In addition, the simulation results show that effectiveness of anomaly traffic detection is enhanced by considering the costs of false errors.