• Title/Summary/Keyword: multi-frame detection

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Implementation of echo canceller for mobile communications interworking switch network (스위치네트워크와 연동에 의한 이동통신용 반향제거장치 구현)

  • 오돈성;이두수
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.21 no.8
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    • pp.2033-2042
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    • 1996
  • In this papre, we describe a recently implemented echo canceller for digital cellular communication of Code Division Multiple Access(CDMA) that features time sharing of digital signal processor(DSP) over four channels in one DSP to reduce per channel costs. In the Public Land Mobile Network(PLMN), it is important to cancel the echo reflected from the Public Switched Telephone Network(PSTN) side. In case of digital mobile system, the round-trip delay of the echo is in excess of about 180 milliseconds due to frame-by-frame voice coding. It is necessary to cancel the echo in PLMN. We have developed a multi-channel echo canceller tht operates with Time Switch Module in a Mobile Switching Center(MSC). The general echo canceller needs PCM trunk interface circuits and the tone detection and disabling circuits, but the multi-channel echo canceller linked with Time Switch Module does not need them. Therefore we could develop the effective and economical echo canceller.

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Feature based Pre-processing Method to compensate color mismatching for Multi-view Video (다시점 비디오의 색상 성분 보정을 위한 특징점 기반의 전처리 방법)

  • Park, Sung-Hee;Yoo, Ji-Sang
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.15 no.12
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    • pp.2527-2533
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    • 2011
  • In this paper we propose a new pre-processing algorithm applied to multi-view video coding using color compensation algorithm based on image features. Multi-view images have a difference between neighboring frames according to illumination and different camera characteristics. To compensate this color difference, first we model the characteristics of cameras based on frame's feature from each camera and then correct the color difference. To extract corresponding features from each frame, we use Harris corner detection algorithm and characteristic coefficients used in the model is estimated by using Gauss-Newton algorithm. In this algorithm, we compensate RGB components of target images, separately from the reference image. The experimental results with many test images show that the proposed algorithm peformed better than the histogram based algorithm as much as 14 % of bit reduction and 0.5 dB ~ 0.8dB of PSNR enhancement.

A Contrastive Learning Framework for Weakly Supervised Video Anomaly Detection

  • Hyeon Jeong Park;Je Hyeong Hong
    • Proceedings of the Korean Society of Broadcast Engineers Conference
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    • 2022.11a
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    • pp.171-174
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    • 2022
  • Weakly-supervised learning is a widely adopted approach in video anomaly detection whereby only video labels are utilized instead of expensive frame-level annotations. Since the success of multi-instance learning (MIL), almost all recent approaches are based on maximizing the margin between the set of abnormal video snippets and those of normal video snippets. In this work, we present a simple contrastive approach for weakly supervised video anomaly detection (WS-VAD) with aims to enhance the performance of existing models. The method is generic in nature and introduces a loss function to encourage attraction of output features from the same video class and repel those from different video classes. Experimental results demonstrate our method can be applied to existing algorithms to improve detection accuracy in public video anomaly dataset.

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Lateral Offset Estimation Based on Detection of Lane Markings

  • Jiang, Gang-Yi;Park, Jong-Wook;Song, Byung-Suk;Bae, Jae-Wook
    • Proceedings of the IEEK Conference
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    • 2000.07b
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    • pp.769-772
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    • 2000
  • In this paper, a new lateral offset estimation method, based on image processing techniques, is proposed for driver assistant system. A new description on lane markings in the image plane is presented, and its properties are discussed and used to detect lane markings. Multi-frame lane detection and analysis are adopted to improve the proposed lateral control method. An algorithm for obstacle detection is also developed. Experimental results show that the proposed method performs lateral control effectively.

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The Study for Improvement Performance on Priority Multi-Buffer Scheme in Wireless LAN (무선 랜에서 우선순위를 할당한 다중 버퍼 사용에 따른 성능 향상에 관한 연구)

  • Kim, Dong-Ok
    • Journal of The Institute of Information and Telecommunication Facilities Engineering
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    • v.3 no.2
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    • pp.42-50
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    • 2004
  • This paper describes a new approach to Internet host mobility. We argue that local mobility, the performance of existing mobile host protocol can be significantly improved. It proposes Fast Moving Detection schemethat based on neighbor AP channel information and moving detection table. And, it composes Local Area Clustering Path (LACP) domain that collected in AP's channel information and MN interface information. It stored the roaming table to include channel information and moving detection. Those which use the proposal scheme will need to put LACP information into the beacon or probe frame. Each AP uses scheme to inform available channel information to MN. From the simulation result, we show that the proposed scheme is advantageous over the legacy schemes in terms of theburst blocking probability and the link utilization.

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Multi-strategy structural damage detection based on included angle of vectors and sparse regularization

  • Liu, Huanlin;Yu, Ling;Luo, Ziwei;Chen, Zexiang
    • Structural Engineering and Mechanics
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    • v.75 no.4
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    • pp.415-424
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    • 2020
  • Recently, many structural damage detection (SDD) methods have been proposed to monitor the safety of structures. As an important modal parameter, mode shape has been widely used in SDD, and the difference of vectors was adopted based on sensitivity analysis and mode shapes in the existing studies. However, amplitudes of mode shapes in different measured points are relative values. Therefore, the difference of mode shapes will be influenced by their amplitudes, and the SDD results may be inaccurate. Focus on this deficiency, a multi-strategy SDD method is proposed based on the included angle of vectors and sparse regularization in this study. Firstly, inspired by modal assurance criterion (MAC), a relationship between mode shapes and changes in damage coefficients is established based on the included angle of vectors. Then, frequencies are introduced for multi-strategy SDD by a weighted coefficient. Meanwhile, sparse regularization is applied to improve the ill-posedness of the SDD problem. As a result, a novel convex optimization problem is proposed for effective SDD. To evaluate the effectiveness of the proposed method, numerical simulations in a planar truss and experimental studies in a six-story aluminum alloy frame in laboratory are conducted. The identified results indicate that the proposed method can effectively reduce the influence of noises, and it has good ability in locating structural damages and quantifying damage degrees.

Design and Implementation of FMCW Radar Based on two-chip for Autonomous Driving Sensor (자율주행센서로서 개발한 2-chip 기반의 FMCW MIMO 레이다 설계 및 구현)

  • Choi, Junhyeok;Park, Shinmyong;Lee, Changhyun;Baek, Seungyeol;Lee, Milim
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.22 no.6
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    • pp.43-49
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    • 2022
  • FMCW(Frequency Modulated Continuous Wave) Radar is very useful for vehicle collision warning system and autonomous driving sensor. In this paper, the design and implementation of FMCW radar based on two chip MMIC developed as an autonomous driving sensor was described. Especially, generation of frame-based and chirp-based waveform generation and signal processing are mixed to have the strength of maximum detection speed and compensation of speed. This implemented system was analyzed for performance and commercialization potential through lab. test and driving test in K-city.

Multi-Style License Plate Recognition System using K-Nearest Neighbors

  • Park, Soungsill;Yoon, Hyoseok;Park, Seho
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.13 no.5
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    • pp.2509-2528
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    • 2019
  • There are various styles of license plates for different countries and use cases that require style-specific methods. In this paper, we propose and illustrate a multi-style license plate recognition system. The proposed system performs a series of processes for license plate candidates detection, structure classification, character segmentation and character recognition, respectively. Specifically, we introduce a license plate structure classification process to identify its style that precedes character segmentation and recognition processes. We use a K-Nearest Neighbors algorithm with pre-training steps to recognize numbers and characters on multi-style license plates. To show feasibility of our multi-style license plate recognition system, we evaluate our system for multi-style license plates covering single line, double line, different backgrounds and character colors on Korean and the U.S. license plates. For the evaluation of Korean license plate recognition, we used a 50 minutes long input video that contains 138 vehicles of 6 different license plate styles, where each frame of the video is processed through a series of license plate recognition processes. From two experiments results, we show that various LP styles can be recognized under 50 ms processing time and with over 99% accuracy, and can be extended through additional learning and training steps.

Performance of the Phoneme Segmenter in Speech Recognition System (음성인식 시스템에서의 음소분할기의 성능)

  • Lee, Gwang-seok
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2009.10a
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    • pp.705-708
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    • 2009
  • This research describes a neural network-based phoneme segmenter for recognizing spontaneous speech. The input of the phoneme segmenter for spontaneous speech is 16th order mel-scaled FFT, normalized frame energy, ratio of energy among 0~3[KHz] band and more than 3[KHz] band. All the features are differences of two consecutive 10 [msec] frame. The main body of the segmenter is single-hidden layer MLP(Multi-Layer Perceptron) with 72 inputs, 20 hidden nodes, and one output node. The segmentation accuracy is 78% with 7.8% insertion.

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Multi-View Wyner-Ziv Video Coding Based on Spatio-temporal Adaptive Estimation (시공간 적응적인 예측에 기초한 다시점 위너-지브 비디오 부호화 기법)

  • Lee, Beom-yong;Kim, Jin-soo
    • The Journal of the Korea Contents Association
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    • v.16 no.6
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    • pp.9-18
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    • 2016
  • This paper proposes a multi-view Wyner-Ziv Video coding scheme based on spatio-temporal adaptive estimation. The proposed algorithm is designed to search for a better estimated block with joint bi-directional motion estimation by introducing weights between temporal and spatial directions, and by classifying effectively the region of interest blocks, which is based on the edge detection and the synthesis, and by selecting the reference estimation block from the effective motion vector analysis. The proposed algorithm exploits the information of a single frame viewpoint and adjacent frame viewpoints, simultaneously and then generates adaptively side information in a variety of closure, and reflection regions to have a better performance. Through several simulations with multi-view video sequences, it is shown that the proposed algorithm performs visual quality improvement as well as bit-rate reduction, compared to the conventional methods.