• Title/Summary/Keyword: Detection Value

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Adaptive Shot Change Detection using Mean of Feature Value on Variable Reference Blocks and Implementation on PMP

  • Kim, Jong-Nam;Kim, Won-Hee
    • Proceedings of the Korean Society of Broadcast Engineers Conference
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    • 2009.01a
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    • pp.229-232
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    • 2009
  • Shot change detection is an important technique for effective management of video data, so detection scheme requires adaptive detection techniques to be used actually in various video. In this paper, we propose an adaptive shot change detection algorithm using the mean of feature value on variable reference blocks. Our algorithm determines shot change detection by defining adaptive threshold values with the feature value extracted from video frames and comparing the feature value and the threshold value. We obtained better detection ratio than the conventional methods maximally by 15% in the experiment with the same test sequence. We also had good detection ratio for other several methods of feature extraction and could see real-time operation of shot change detection in the hardware platform with low performance was possible by implementing it in TVUS model of HOMECAST Company. Thus, our algorithm in the paper can be useful in PMP or other portable players.

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Adaptive Shot Change Detection Technique Using Mean of Feature Value on Variable Reference Block (가변 참조 구간의 평균 특징값을 이용한 적응적인 장면 전환 검출 기법)

  • Kim, Won-Hee;Moon, Kwang-Seok;Kim, Jong-Nam
    • Journal of the Institute of Convergence Signal Processing
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    • v.9 no.4
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    • pp.272-279
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    • 2008
  • Shot change detection is an important technique for effective management of video data, so detection scheme requires adaptive detection techniques to be used actually in various video. In this paper, we propose an adaptive shot change detection algorithm using the mean of feature value on variable reference blocks. Our algorithm determines shot change detection by defining adaptive threshold values with the feature value extracted from video frames and comparing the feature value and the threshold value. We obtained better detection ratio than the conventional methods maximally by 15% in the experiment with the same test sequence. We also had good detection ratio for other several methods of feature extraction and could see realtime operation of shot change detection in the hardware platform with low performance was possible by implementing it in TVUS model of HOMECAST company. Thus, our algerian in the paper can be useful in PMP(portable multimedia player) or other portable players.

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A Simple and Robustness Algorithm for ECG R- peak Detection

  • Rahman, Md Saifur;Choi, Chulhyung;Kim, Young-pil;Kim, Sikyung
    • Journal of Electrical Engineering and Technology
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    • v.13 no.5
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    • pp.2080-2085
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    • 2018
  • There have been numerous studies that extract the R-peak from electrocardiogram (ECG) signals. All of these studies can extract R-peak from ECG. However, these methods are complicated and difficult to implement in a real-time portable ECG device. After filtration choosing a threshold value for R-peak detection is a big challenge. Fixed threshold scheme is sometimes unable to detect low R-peak value and adaptive threshold sometime detect wrong R-peak for more adaptation. In this paper, a simple and robustness algorithm is proposed to detect R-peak with less complexity. This method also solves the problem of threshold value selection. Using the adaptive filter, the baseline drift can be removed from ECG signal. After filtration, an appropriate threshold value is automatically chosen by using the minimum and maximum value of an ECG signals. Then the neighborhood searching scheme is applied under threshold value to detect R-peak from ECG signals. Proposed method improves the detection and accuracy rate of R-peak detection. After R-peak detection, we calculate heart rate to know the heart condition.

Multiple Plane Area Detection Using Self Organizing Map (자기 조직화 지도를 이용한 다중 평면영역 검출)

  • Kim, Jeong-Hyun;Teng, Zhu;Kang, Dong-Joong
    • Journal of Institute of Control, Robotics and Systems
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    • v.17 no.1
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    • pp.22-30
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    • 2011
  • Plane detection is very important information for mission-critical of robot in 3D environment. A representative method of plane detection is Hough-transformation. Hough-transformation is robust to noise and makes the accurate plane detection possible. But it demands excessive memory and takes too much processing time. Iterative randomized Hough-transformation has been proposed to overcome these shortcomings. This method doesn't vote all data. It votes only one value of the randomly selected data into the Hough parameter space. This value calculated the value of the parameter of the shape that we want to extract. In Hough parameters space, it is possible to detect accurate plane through detection of repetitive maximum value. A common problem in these methods is that it requires too much computational cost and large number of memory space to find the distribution of mixed multiple planes in parameter space. In this paper, we detect multiple planes only via data sampling using Self Organizing Map method. It does not use conventional methods that include transforming to Hough parameter space, voting and repetitive plane extraction. And it improves the reliability of plane detection through division area searching and planarity evaluation. The proposed method is more accurate and faster than the conventional methods which is demonstrated the experiments in various conditions.

Variable Dynamic Threshold Method for Video Cut Detection (동영상 컷 검출을 위한 가변형 동적 임계값 기법)

  • 염성주;김우생
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.27 no.4A
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    • pp.356-363
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    • 2002
  • Video scene segmentation is fundamental role for content based video analysis and many kinds of scene segmentation schemes have been proposed in previous researches. However, there is a problem, which is to find optimal threshold value according to various kinds of movies and its content because only fixed single threshold value usually used for cut detection. In this paper, we proposed the variable dynamic threshold method, which change the threshold value by a probability distribution of cut detection interval and information of frame feature differences and cut detection interval in previous cut detection is used to determine the next cut detection. For this, we present a cut detection algorithm and a parameter generation method to change the threshold value in runtime. We also show the proposed method, which can minimize fault alarm rate than the existing methods efficiently by experimental results.

The Generation of a TM Mask Using the AM Technique and the Edge Detection Algorithm for a SAR Image (AM 기법을 이용한 TM 마스크의 형성 및 SAR 영상의 경계검출 알고리듬)

  • 한수용;최성진;라극환
    • Journal of the Korean Institute of Telematics and Electronics B
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    • v.29B no.4
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    • pp.36-47
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    • 1992
  • In this paper, a set of TM(template matching) mask using the AM(associative mapping) technique was generated and the edge detection algorithm for a SAR image was proposed. And also, the performance of the proposed edge detection algorithm was tested with the conventional edge detection techniques. The proposed edge detection algorithm created an edge image which was more accurate and clear than the conventional edge detection techniques and the performance of the proposed detection technique was not deteriorated for low intensity area in the image because the uncertainly thresholded value genetated by the conventional detection methods was requested. Also, the number of masks and the detection time were reduced by adjusting resolution of edge detection and the consideration for the threshold value extracting the edge was very intuitive.

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Face Detection by Eye Detection with Progressive Thresholding

  • Jung, Ji-Moon;Kim, Tae-Chul;Wie, Eun-Young;Nam, Ki-Gon
    • 제어로봇시스템학회:학술대회논문집
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    • 2005.06a
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    • pp.1689-1694
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    • 2005
  • Face detection plays an important role in face recognition, video surveillance, and human computer interface. In this paper, we present a face detection system using eye detection with progressive thresholding from a digital camera. The face candidate is detected by using skin color segmentation in the YCbCr color space. The face candidates are verified by detecting the eyes that is located by iterative thresholding and correlation coefficients. Preprocessing includes histogram equalization, log transformation, and gray-scale morphology for the emphasized eyes image. The distance of the eye candidate points generated by the progressive increasing threshold value is employed to extract the facial region. The process of the face detection is repeated by using the increasing threshold value. Experimental results show that more enhanced face detection in real time.

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Intrusion Detection Algorithm in Mobile Ad-hoc Network using CP-SVM (Mobile Ad - hoc Network에서 CP - SVM을 이용한 침입탐지)

  • Yang, Hwan Seok
    • Journal of Korea Society of Digital Industry and Information Management
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    • v.8 no.2
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    • pp.41-47
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    • 2012
  • MANET has vulnerable structure on security owing to structural characteristics as follows. MANET consisted of moving nodes is that every nodes have to perform function of router. Every node has to provide reliable routing service in cooperation each other. These properties are caused by expose to various attacks. But, it is difficult that position of environment intrusion detection system is established, information is collected, and particularly attack is detected because of moving of nodes in MANET environment. It is not easy that important profile is constructed also. In this paper, conformal predictor - support vector machine(CP-SVM) based intrusion detection technique was proposed in order to do more accurate and efficient intrusion detection. In this study, IDS-agents calculate p value from collected packet and transmit to cluster head, and then other all cluster head have same value and detect abnormal behavior using the value. Cluster form of hierarchical structure was used to reduce consumption of nodes also. Effectiveness of proposed method was confirmed through experiment.

Emerging Topic Detection Using Text Embedding and Anomaly Pattern Detection in Text Streaming Data (텍스트 스트리밍 데이터에서 텍스트 임베딩과 이상 패턴 탐지를 이용한 신규 주제 발생 탐지)

  • Choi, Semok;Park, Cheong Hee
    • Journal of Korea Multimedia Society
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    • v.23 no.9
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    • pp.1181-1190
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    • 2020
  • Detection of an anomaly pattern deviating normal data distribution in streaming data is an important technique in many application areas. In this paper, a method for detection of an newly emerging pattern in text streaming data which is an ordered sequence of texts is proposed based on text embedding and anomaly pattern detection. Using text embedding methods such as BOW(Bag Of Words), Word2Vec, and BERT, the detection performance of the proposed method is compared. Experimental results show that anomaly pattern detection using BERT embedding gave an average F1 value of 0.85 and the F1 value of 1 in three cases among five test cases.

Application of Multiple Threshold Values for Accuracy Improvement of an Automated Binary Change Detection Model

  • Yu, Byeong-Hyeok;Chi, Kwang-Hoon
    • Korean Journal of Remote Sensing
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    • v.25 no.3
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    • pp.271-285
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    • 2009
  • Multi-temporal satellite imagery can be changed into a transform image that emphasizes the changed area only through the application of various change detection techniques. From the transform image, an automated change detection model calculates the optimal threshold value for classifying the changed and unchanged areas. However, the model can cause undesirable results when the histogram of the transform image is unbalanced. This is because the model uses a single threshold value in which the sign is either positive or negative and its value is constant (e.g. -1, 1), regardless of the imbalance between changed pixels. This paper proposes an advanced method that can improve accuracy by applying separate threshold values according to the increased or decreased range of the changed pixels. It applies multiple threshold values based on the cumulative producer's and user's accuracies in the automated binary change detection model, and the analyst can automatically extract more accurate optimal threshold values. Multi-temporal IKONOS satellite imagery for the Daejeon area was used to test the proposed method. A total of 16 transformation results were applied to the two study sites, and optimal threshold values were determined using accuracy assessment curves. The experiment showed that the accuracy of most transform images is improved by applying multiple threshold values. The proposed method is expected to be used in various study fields, such as detection of illegal urban building, detection of the damaged area in a disaster, etc.