• Title/Summary/Keyword: Detection Space

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A Track Scoring Function Development for Airborne Target Detection Using Dynamic Programming

  • Won, Dae-Yeon;Shim, Sang-Wook;Kim, Keum-Seong;Tahk, Min-Jea;Kim, Eung-Tai
    • International Journal of Aeronautical and Space Sciences
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    • v.13 no.1
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    • pp.99-105
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    • 2012
  • Track-before-detect techniques based on dynamic programming have provided solutions for detecting targets from a sequence of images. In its application to airborne threat detection, dynamic programming solutions should take into account the distinguishable properties of objects in a collision course. This paper describes the development of a new track scoring function that accumulates scores for airborne targets in Bayesian framework. Numerical results show that the proposed scoring function has slightly better detection capabilities.

Edge Detection Method Based on Neural Networks for COMS MI Images

  • Lee, Jin-Ho;Park, Eun-Bin;Woo, Sun-Hee
    • Journal of Astronomy and Space Sciences
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    • v.33 no.4
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    • pp.313-318
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    • 2016
  • Communication, Ocean And Meteorological Satellite (COMS) Meteorological Imager (MI) images are processed for radiometric and geometric correction from raw image data. When intermediate image data are matched and compared with reference landmark images in the geometrical correction process, various techniques for edge detection can be applied. It is essential to have a precise and correct edged image in this process, since its matching with the reference is directly related to the accuracy of the ground station output images. An edge detection method based on neural networks is applied for the ground processing of MI images for obtaining sharp edges in the correct positions. The simulation results are analyzed and characterized by comparing them with the results of conventional methods, such as Sobel and Canny filters.

The Space Vector Detection based Three-Phase Hybrid Series Active Power Filter for Compensating Dynamic Voltage Sag and Harmonic Current (순시전압 sag 및 고조파 전류 보상을 위한 공간벡터 검출법 기반의 3상 하이브리드 직렬형 능동전력필터)

  • 양승환;정영국;임영철
    • The Transactions of the Korean Institute of Power Electronics
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    • v.9 no.4
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    • pp.303-310
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    • 2004
  • In this paper, for compensating dynamic voltage sag and harmonic current, 3-phase hybrid series active power filter based on the space vector detection is proposed. The Space vector algorithm for detecting the voltage sag and the harmonic current in compared with conventional theory is a simple method for calculating the compensating reference without any coordinated transformation. The effectiveness of the proposed system is verified by the PSIM simulation in the steady state and the transient state, which the proposed system is able to simultaneously compensate harmonics and source voltage unbalance / sag.

Error Control Coding and Space-Time MMSE Multiuser Detection in DS-CDMA Systems

  • Hamouda, Walaa;McLane, Peter J.
    • Journal of Communications and Networks
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    • v.5 no.3
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    • pp.187-196
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    • 2003
  • We consider the use of error control coding in direct sequence-code-division multiple access (OS-COMA) systems that employ multiuser detection (MUO) and space diversity. The relative performance gain between Reed-Solomon (RS) code and convolutional code (CC) is well known in [1] for the single user, additive white Gaussian noise (AWGN) channel. In this case, RS codes outperform CC's at high signal-to-noise ratios. We find that this is not the case for the multiuser interference channel mentioned above. For useful error rates, we find that soft-decision CC's to be uniformly better than RS codes when used with DS-COMA modulation in multiuser space-time channels. In our development, we use the Gaussian approximation on the interference to determine performance error bounds for systems with low number of users. Then, we check their accuracy in error rate estimation via system's simulation. These performance bounds will in turn allow us to consider a large number of users where we can estimate the gain in user-capacity due to channel coding. Lastly, the use of turbo codes is considered where it is shown that they offer a coding gain of 2.5 dB relative to soft-decision CC.

Improved Differential Detection Scheme of Space Time Trellis Coded MDPSK For MIMO (MIMO에서 시공간 부호화된 MDPSK의 성능을 향상시키기 위한 차동 검파 시스템)

  • Kim, Chong-Il;Lee, Ho-Jin;Yoo, Hang-Youal;Kim, Jin-Yong;Kim, Seung-Youal
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • v.9 no.2
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    • pp.164-167
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    • 2005
  • Recently, STC techniques have been considered to be candidate to support multimedia services in the next generation mobile radio communications and have been developed the many communications systems in order to achieve the high data rates. In this paper, we propose the Trellis-Coded Differential Space Time Modulation system with multiple symbol detection. The Trellis-code performs the set partition with unitary group codes. The Viterbi decoder containing new branch metrics is introduced in order to improve the bit error rate (BER) in the differential detection of the unitary differential space time modulation. Also, we describe the Viterbi algorithm in order to use this branch metrics. Our study shows that such a Viterbi decoder improves BER performance without sacrificing bandwidth and power efficiency.

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High Speed Face Detection Using Skin Color (살색을 이용한 고속 얼굴검출 알고리즘의 개발)

  • 한영신;박동식;이칠기
    • Proceedings of the IEEK Conference
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    • 2002.06c
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    • pp.173-176
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    • 2002
  • This paper describes an implementation of fast face detection algorithm. This algorithm can robustly detect human faces with unknown sizes and positions in complex backgrounds. This paper provides a powerful face detection algorithm using skin color segmenting. Skin Color is modeled by a Gaussian distribution in the HSI color space among different persons within the same race, Oriental. The main feature of the Algorithm is achieved face detection robust to illumination changes and a simple adaptive thresholding technique for skin color segmentation is employed to achieve robust face detection.

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Symmetry Detection Through Hybrid Use Of Location And Direction Of Edges

  • Koo, Ja Young
    • Journal of the Korea Society of Computer and Information
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    • v.21 no.4
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    • pp.9-15
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    • 2016
  • Symmetry is everywhere in the world around us from galaxy to microbes. From ancient times symmetry is considered to be a reflection of the harmony of universe. Symmetry is not only a significant clue for human cognitive process, but also useful information for computer vision such as image understanding system. Application areas include face detection and recognition, indexing of image database, image segmentation and detection, analysis of medical images, and so on. The technique used in this paper extracts edges, and the perpendicular bisector of any two edge points is considered to be a candidate axis of symmetry. The coefficients of candidate axis are accumulated in the coefficient space. Then the axis of symmetry is determined to be the line for which the coefficient histogram has maximum value. In this paper, an improved method is proposed that utilizes the directional information of edges, which is a byproduct of the edge detection process. Experiment on 20 test images shows that the proposed method performs 22.7 times faster than the original method. In another test on 5 images with 4% salt-and-pepper noise, the proposed method detects the symmetry successfully, while the original method fails. This result reveals that the proposed method enhances the speed and accuracy of detection process at the same time.

A Study on Realtime Drone Object Detection Using On-board Deep Learning (온-보드에서의 딥러닝을 활용한 드론의 실시간 객체 인식 연구)

  • Lee, Jang-Woo;Kim, Joo-Young;Kim, Jae-Kyung;Kwon, Cheol-Hee
    • Journal of the Korean Society for Aeronautical & Space Sciences
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    • v.49 no.10
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    • pp.883-892
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    • 2021
  • This paper provides a process for developing deep learning-based aerial object detection models that can run in realtime on onboard. To improve object detection performance, we pre-process and augment the training data in the training stage. In addition, we perform transfer learning and apply a weighted cross-entropy method to reduce the variations of detection performance for each class. To improve the inference speed, we have generated inference acceleration engines with quantization. Then, we analyze the real-time performance and detection performance on custom aerial image dataset to verify generalization.