• Title/Summary/Keyword: correlation detection

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Deep Learning Object Detection to Clearly Differentiate Between Pedestrians and Motorcycles in Tunnel Environment Using YOLOv3 and Kernelized Correlation Filters

  • Mun, Sungchul;Nguyen, Manh Dung;Kweon, Seokkyu;Bae, Young Hoon
    • Journal of Broadcast Engineering
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    • v.24 no.7
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    • pp.1266-1275
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    • 2019
  • With increasing criminal rates and number of CCTVs, much attention has been paid to intelligent surveillance system on the horizon. Object detection and tracking algorithms have been developed to reduce false alarms and accurately help security agents immediately response to undesirable changes in video clips such as crimes and accidents. Many studies have proposed a variety of algorithms to improve accuracy of detecting and tracking objects outside tunnels. The proposed methods might not work well in a tunnel because of low illuminance significantly susceptible to tail and warning lights of driving vehicles. The detection performance has rarely been tested against the tunnel environment. This study investigated a feasibility of object detection and tracking in an actual tunnel environment by utilizing YOLOv3 and Kernelized Correlation Filter. We tested 40 actual video clips to differentiate pedestrians and motorcycles to evaluate the performance of our algorithm. The experimental results showed significant difference in detection between pedestrians and motorcycles without false positive rates. Our findings are expected to provide a stepping stone of developing efficient detection algorithms suitable for tunnel environment and encouraging other researchers to glean reliable tracking data for smarter and safer City.

Multimedia Watermark Detection Algorithm Based on Bayes Decision Theory (Bayes 판단 이론 기반 멀티미디어 워터마크 검출 알고리즘)

  • 권성근;이석환;김병주;권기구;하인성;권기룡;이건일
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.27 no.7A
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    • pp.695-704
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    • 2002
  • Watermark detection plays a crucial role in multimedia copyright protection and has traditionally been tackled using correlation-based algorithms. However, correlation-based detection is not actually the best choice, as it does not utilize the distributional characteristics of the image being marked. Accordingly, an efficient watermark detection scheme for DWT coefficients is proposed as optimal for non-additive schemes. Based on the statistical decision theory, the proposed method is derived according to Bayes decision theory, the Neyman-Pearson criterion, and the distribution of the DWT coefficients, thereby minimizing the missed detection probability subject to a given false alarm probability. The proposed method was tested in the context of robustness, and the results confirmed the superiority of the proposed technique over conventional correlation-based detection method.

Watermark Detection Algorithm Using Statistical Decision Theory (통계적 판단 이론을 이용한 워터마크 검출 알고리즘)

  • 권성근;김병주;이석환;권기구;권기용;이건일
    • Journal of the Institute of Electronics Engineers of Korea CI
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    • v.40 no.1
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    • pp.39-49
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    • 2003
  • Watermark detection has a crucial role in copyright protection of and authentication for multimedia and has classically been tackled by means of correlation-based algorithms. Nevertheless, when watermark embedding does not obey an additive rule, correlation-based detection is not the optimum choice. So a new detection algorithm is proposed which is optimum for non-additive watermark embedding. By relying on statistical decision theory, the proposed method is derived according to the Bayes decision theory, Neyman-Pearson criterion, and distribution of wavelet coefficients, thus permitting to minimize the missed detection probability subject to a given false detection probability. The superiority of the proposed method has been tested from a robustness perspective. The results confirm the superiority of the proposed technique over classical correlation- based method.

Design and Performance Evaluation of GPS Spoofing Signal Detection Algorithm at RF Spoofing Simulation Environment

  • Lim, Soon;Lim, Deok Won;Chun, Sebum;Heo, Moon Beom;Choi, Yun Sub;Lee, Ju Hyun;Lee, Sang Jeong
    • Journal of Positioning, Navigation, and Timing
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    • v.4 no.4
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    • pp.173-180
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    • 2015
  • In this study, an algorithm that detects a spoofing signal for a GPS L1 signal was proposed, and the performance was verified through RF spoofing signal simulation. The proposed algorithm determines the reception of a spoofing signal by detecting a correlation distortion of GPS L1 C/A code caused by the spoofing signal. To detect the correlation distortion, a detection criterion of a spoofing signal was derived from the relationship among the Early, Prompt, and Late tap correlation values of a receiver correlator; and a detection threshold was calculated from the false alarm probability of spoofing signal detection. In this study, an RF spoofing environment was built using the GSS 8000 simulator (Spirent). For the RF spoofing signal generated from the simulator, the RF spoofing environment was verified using the commercial receiver DL-V3 (Novatel Inc.). To verify the performance of the proposed algorithm, the RF signal was stored as IF band data using a USRP signal collector (NI) so that the data could be processed by a CNU software receiver (software defined radio). For the performance of the proposed algorithm, results were obtained using the correlation value of the software receiver, and the performance was verified through the detection of a spoofing signal and the detection time of a spoofing signal.

Structure Detection of Transmission Frame Based on Accumulated Correlation for DVB-S2 System (DVB-S2 시스템에서 상관 누적을 이용한 전송프레임 구조 검출)

  • Jeon, Hanik;Oh, Deock-Gil
    • Journal of Satellite, Information and Communications
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    • v.10 no.2
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    • pp.109-114
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    • 2015
  • Frame synchronization is achieved by correlation between received symbols and a preamble pattern which is periodically appended at a frame header. In this paper, we deal with a frame detection method complaint with satellite-based DVB-S2 system. In DVB-S2, frame synchronization is performed under the low signal-to-noise ratio(SNR), a large frequency offset which can be up to 20% of a symbol transmission rate and unknown modulation schemes ranging from QPSK to 32-APSK. In this environment, we propose a method combining differential correlation based on SOF and PLSC with an accumulated correlation method for the detection of frame structures. In addition, detection performances about mean acquisition time(MAT) and detection error probability are evaluated via computer simulations.

Design of GPS L1 C/A Spoofing Signal Detection Algorithm (GPS L1 C/A 기만 신호 검출 기법 설계)

  • Lim, Soon;Lim, Deok-Won;Heo, Moon-Beom;Nam, Gi-Wook
    • Journal of Advanced Navigation Technology
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    • v.18 no.1
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    • pp.7-13
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    • 2014
  • In this paper, an effect on a GPS receiver by spoofing signal is analyzed and a GPS spoofing signal detection algorithm for GPS L1 C/A spoofing signal is proposed. A proposed detection algorithm monitors the correlation function distortion by the spoofing signal. If detected distortion is over a detection threshold, we can determine that the spoofing signal is received. The detection threshold is calculated from the statistical characteristics of a thermal noise. For verifying the suggested algorithm, a MATLAB-based simulation platform is implemented. This platform has functionalities to track GPS signal and measure the correlation values. By using this platform, the correlation function distortion by spoofing signal is observed. Also a performance of the algorithm proposed in this paper is applied and confirm the detection of a spoofing signal.

Efficient Forest Fire Detection using Rule-Based Multi-color Space and Correlation Coefficient for Application in Unmanned Aerial Vehicles

  • Anh, Nguyen Duc;Van Thanh, Pham;Lap, Doan Tu;Khai, Nguyen Tuan;Van An, Tran;Tan, Tran Duc;An, Nguyen Huu;Dinh, Dang Nhu
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.16 no.2
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    • pp.381-404
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    • 2022
  • Forest fires inflict great losses of human lives and serious damages to ecological systems. Hence, numerous fire detection methods have been proposed, one of which is fire detection based on sensors. However, these methods reveal several limitations when applied in large spaces like forests such as high cost, high level of false alarm, limited battery capacity, and other problems. In this research, we propose a novel forest fire detection method based on image processing and correlation coefficient. Firstly, two fire detection conditions are applied in RGB color space to distinguish between fire pixels and the background. Secondly, the image is converted from RGB to YCbCr color space with two fire detection conditions being applied in this color space. Finally, the correlation coefficient is used to distinguish between fires and objects with fire-like colors. Our proposed algorithm is tested and evaluated on eleven fire and non-fire videos collected from the internet and achieves up to 95.87% and 97.89% of F-score and accuracy respectively in performance evaluation.

Two Wheeler Recognition Using the Correlation Coefficient for Histogram of Oriented Gradients to Apply Intelligent Wheelchair (지능형 휠체어 적용을 위한 기울기 히스토그램의 상관계수를 이용한 도로위의 이륜차 인식)

  • Kim, Bum-Koog;Park, Sang-Hee;Lee, Yeung-Hak;Lee, Gang-Hwa
    • Journal of Biomedical Engineering Research
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    • v.32 no.4
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    • pp.336-344
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    • 2011
  • This article describes a new recognition algorithm using correlation coefficient for intelligent wheelchair to avoid collision for elderly or disabled people. The correlation coefficient can be used to represent the relationship of two different areas. The algorithm has three steps: Firstly, we extract an edge vector using the Histogram of Oriented Gradients(HOG) which includes gradient information and unique magnitude for each cell. From this result, the correlation coefficients are calculated between one cell and others. Secondly, correlation coefficients are used as the weighting factors for normalizing the HOG cell. And finally, these features are used to classify or detect variable and complicated shapes of two wheelers using Adaboost algorithm. In this paper, we propose a new feature vectors which is calculated by weighted cell unit to classify with multiple view-based shapes: frontal, rear and side views($60^{\circ}$, $90^{\circ}$ and mixed angle). Our experimental results show that two wheeler detection system based on a proposed approach leads to a higher detection accuracy than the method using traditional features in a similar detection time.

New Approach to Two-wheeler Detection using Correlation Coefficient based on Histogram of Oriented Gradients

  • Lee, Yeunghak;Shim, Jaechang
    • Journal of Multimedia Information System
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    • v.3 no.4
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    • pp.119-128
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    • 2016
  • This study aims to suggest a new algorithm for detecting two-wheelers on road that have various shapes according to the viewing angle for vision based intelligent vehicles. This article describes a new approach to two-wheelers detection algorithm riding on people based on modified Histogram of Oriented Gradients (HOG) using correlation coefficient (CC). The CC between two local area variables, in which one is the person riding a bike and other is its background, can represent correlation relation. First, we extract edge vectors using HOG which includes gradient information and differential magnitude as cell based. And then, the value, which is calculated by the CC between the area of each cell and one of two-wheelers, can be extracted as the weighting factor in process for normalizing the modified HOG cell. This paper applied the Adaboost algorithm to make a strong classification from weak classification. In this experiment, we can get the result that the detection rate of the proposed method is higher than that of the traditional method.

An Algorithm for Leak Locating using Coupled Vibration of Pipe-Water (배관-유체 연성진동을 이용한 누수지점 탐지알고리듬 개발연구)

  • Lee, Yeong-Seop;Yun, Dong-Jin
    • Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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    • 2004.05a
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    • pp.985-990
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    • 2004
  • Leak noise is a good source to identify the exact location of a leak point of underground water pipelines. Water leak generates broadband noise from a leak location and can be propagated to both directions of water pipes. This sound propagation due to leak in water pipelines is not a non-dispersive wave any more because of the surrounding pipes and soil. However, the necessity of long-range detection of this leak location makes to identify low-frequency acoustic waves rather than high frequency ones. Acoustic wave propagation coupled with surrounding boundaries including cast iron pipes is theoretically analyzed and the wave velocity was confirmed with experiment. The leak locations were identified both by the acoustic emission (AE) method and the cross-correlation method. In a short-range distance, both the AE method and cross-correlation method are effective to detect leak position. However, the detection for a long-range distance required a lower frequency range accelerometers only because higher frequency waves were attenuated very quickly with the increase of propagation paths. Two algorithms for the cross-correlation function were suggested, and a long-range detection has been achieved at real underground water pipelines longer than 300m.

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