• Title/Summary/Keyword: Frame Subtraction

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People Counting System using Raspberry Pi

  • Ansari, Md Israfil;Shim, Jaechang
    • Journal of Multimedia Information System
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    • v.4 no.4
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    • pp.239-242
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    • 2017
  • This paper proposes a low-cost method for counting people based on blob detection and blob tracking. Here background subtraction is used to detected blob and then the blob is classified with its width and height to specify that the blob is a person. In this system we first define the area of entry and exit point in the video frame. The counting of people starts when midpoint of the people blob crosses the defined point. Finally, total number of people entry and exit from the place is displayed. Experiment result of this proposed system has high accuracy in real-time performance.

Face and Hand Activity Detection Based on Haar Wavelet and Background Updating Algorithm

  • Shang, Yiting;Lee, Eung-Joo
    • Journal of Korea Multimedia Society
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    • v.14 no.8
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    • pp.992-999
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    • 2011
  • This paper proposed a human body posture recognition program based on haar-like feature and hand activity detection. Its distinguishing features are the combination of face detection and motion detection. Firstly, the program uses the haar-like feature face detection to receive the location of human face. The haar-like feature is provided with the advantages of speed. It means the less amount of calculation the haar-like feature can exclude a large number of interference, and it can discriminate human face more accurately, and achieve the face position. Then the program uses the frame subtraction to achieve the position of human body motion. This method is provided with good performance of the motion detection. Afterwards, the program recognises the human body motion by calculating the relationship of the face position with the position of human body motion contour. By the test, we know that the recognition rate of this algorithm is more than 92%. The results show that, this algorithm can achieve the result quickly, and guarantee the exactitude of the result.

Performance Improvement of SPLICE-based Noise Compensation for Robust Speech Recognition (강인한 음성인식을 위한 SPLICE 기반 잡음 보상의 성능향상)

  • Kim, Hyung-Soon;Kim, Doo-Hee
    • Speech Sciences
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    • v.10 no.3
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    • pp.263-277
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    • 2003
  • One of major problems in speech recognition is performance degradation due to the mismatch between the training and test environments. Recently, Stereo-based Piecewise LInear Compensation for Environments (SPLICE), which is frame-based bias removal algorithm for cepstral enhancement using stereo training data and noisy speech model as a mixture of Gaussians, was proposed and showed good performance in noisy environments. In this paper, we propose several methods to improve the conventional SPLICE. First we apply Cepstral Mean Subtraction (CMS) as a preprocessor to SPLICE, instead of applying it as a postprocessor. Secondly, to compensate residual distortion after SPLICE processing, two-stage SPLICE is proposed. Thirdly we employ phonetic information for training SPLICE model. According to experiments on the Aurora 2 database, proposed method outperformed the conventional SPLICE and we achieved a 50% decrease in word error rate over the Aurora baseline system.

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Medical Image Data Compression Based on the Region Segmentation (영역분할을 기반으로 한 의료영상 데이타 압축)

  • 김진태;두경수
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.3 no.3
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    • pp.597-605
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    • 1999
  • In this paper, we propose a cardioangiography sequence image coding scheme which use a subtraction between initial image and current frame inserted contrast dye. Stable regions are obtained by the multithreshold and meaningful region is extracted by the images with stable region. The image with meaningful region is classified into contour and texture information. Contour information is coded by contour coding. And texture information is approximated by two-dimensional polynomial function and each coefficients is coded. Experimental results confirm that the sequence of cardioangiography are well reconstructed at the low bit rate (0.02∼0.04 bpp) and high compression ratio.

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Improved non-parametric Model for Moving object segmentation by null hypothesis (귀무가설을 이용한 비모수 움직임 영상 검출 모델의 개선)

  • Lee, Ki-Sun;Na, Sang-Il;Lee, Jun-Woo;Jeong, Dong-Seok
    • Proceedings of the IEEK Conference
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    • 2007.07a
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    • pp.249-250
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    • 2007
  • Background subtraction is a method typically used to segment moving regions in image sequences taken from a static camera by comparing each new frame to a model of the scene background. We present a improved non-parametric background model by null hypothesis. Evaluation shows that this approach achieves very sensitive detection with very low false alarm rates.

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Improvement of Background Subtraction Algorithm using Intra-Frame Global Background Model (프레임 내 전체 배경 모델을 이용한 배경 분리 알고리즘의 정확도 개선)

  • Lee, Sang-Hoon;Kim, Gibak;Cho, Nam Ik
    • Proceedings of the Korean Society of Broadcast Engineers Conference
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    • 2014.11a
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    • pp.160-163
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    • 2014
  • 본 논문에서는 프레임 내 전체 배경 모델을 도입하여 기존 배경 분리 알고리즘에서의 오검출을 줄여 정확도를 개선하고자 한다. 기존의 알고리즘은 프레임 간의 정보만을 이용하여 배경 확률 모델을 만들고 배경을 제외한 전경만을 검출한다. 제안하는 알고리즘에서는 먼저 기존의 알고리즘을 통해 프레임 간의 정보를 이용하여 간단하게 배경과 전경을 분리한다. 그 후 프레임 내 정보를 통해 전체 배경 모델을 만들고, 앞의 결과에서 한번 더 배경을 제외함으로써 검출 정확도를 개선하고자 한다. 실험결과에서 Change Detection Workshop dataset에 대해 실험을 한 후 결과 영상 비교 및 F-measure 를 통해 개선된 결과를 확인할 수 있다.

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Efficient Learning and Classification for Vehicle Type using Moving Cast Shadow Elimination in Vehicle Surveillance Video (차량 감시영상에서 그림자 제거를 통한 효율적인 차종의 학습 및 분류)

  • Shin, Wook-Sun;Lee, Chang-Hoon
    • The KIPS Transactions:PartB
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    • v.15B no.1
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    • pp.1-8
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    • 2008
  • Generally, moving objects in surveillance video are extracted by background subtraction or frame difference method. However, moving cast shadows on object distort extracted figures which cause serious detection problems. Especially, analyzing vehicle information in video frames from a fixed surveillance camera on road, we obtain inaccurate results by shadow which vehicle causes. So, Shadow Elimination is essential to extract right objects from frames in surveillance video. And we use shadow removal algorithm for vehicle classification. In our paper, as we suppress moving cast shadow in object, we efficiently discriminate vehicle types. After we fit new object of shadow-removed object as three dimension object, we use extracted attributes for supervised learning to classify vehicle types. In experiment, we use 3 learning methods {IBL, C4.5, NN(Neural Network)} so that we evaluate the result of vehicle classification by shadow elimination.

A Small-area Hardware Implementation of EGML-based Moving Object Detection Processor (EGML 기반 이동객체 검출 프로세서의 저면적 하드웨어 구현)

  • Sung, Mi-ji;Shin, Kyung-wook
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.21 no.12
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    • pp.2213-2220
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    • 2017
  • This paper proposes an efficient approach for hardware implementation of moving object detection (MOD) processor using effective Gaussian mixture learning (EGML)-based background subtraction method. Arithmetic units used in background generation were implemented using LUT-based approximation to reduce hardware complexity. Hardware resources used for both background subtraction and Gaussian probability density calculation were shared. The MOD processor was verified by FPGA-in-the-loop simulation using MATLAB/Simulink. The MOD performance was evaluated by using six types of video defined in IEEE CDW-2014 dataset, which resulted the average of recall value of 0.7700, the average of precision value of 0.7170, and the average of F-measure value of 0.7293. The MOD processor was implemented with 882 slices and block RAM of $146{\times}36kbits$ on Virtex5 FPGA, resulting in 60% hardware reduction compared to conventional design based on EGML. It was estimated that the MOD processor could operate with 75 MHz clock, resulting in real-time processing of $800{\times}600$ video with a frame rate of 39 fps.

Performance Improvement of Speech Enhancement Using Independent Component Analysis and Perceptual Filtering (독립 성분 분석과 지각 필터를 이용한 음질 개선)

  • Koo, Kyo-Sik;Cha, Hyung-Tai
    • The Journal of the Acoustical Society of Korea
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    • v.29 no.4
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    • pp.270-277
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    • 2010
  • In this paper, we proposed an algorithm that improves tone quality of noisy audio signals by using ICA(Independent Component Analysis) algorithm and perceptual filters. Many algorithms have been proposed to eliminate the noise from the audio signals, such as spectral subtraction method, perceptual filter, etc. The perceptual filter uses a noise that is acquired from silent ranges in the input signal. In this case, the improvement rate of tone quality decreases if the noise energy is changed by the environmental variation in a signal frame. But the proposed method estimates a noise that is changed at each frame using ICA algorithm. The estimated noise is applied to perceptual filter. To show the performance of the proposed algorithm, several tests are performed to various input signals. With the proposed algorithm, we could confirm the enhancement of tone quality in terms of segmental SNR (SSNR), noise-to-mask ratio (NMR) and Degradation Category Rating (DCR) test.

Development of the Whole Body 3-Dimensional Topographic Radiotherapy System (3차원 전신 정위 방사선 치료 장치의 개발)

  • Jung, Won-Kyun;Lee, Byung-Yong;Choi, Eun-Kyung;Kim, Jong-Hoon;An, Seung-Do;Lee, Seok;Min, Chul-Ki;Park, Cham-Bok;Jang, Hye-Sook
    • Progress in Medical Physics
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    • v.10 no.2
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    • pp.63-71
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    • 1999
  • For the purpose of utilization in 3-D conformal radiotherapy and whole body radiosurgery, the Whole Body 3-Dimensional Topographic Radiation Therapy System has been developed. Whole body frame was constructed in order to be installed on the couch. Radiopaque catheters were engraved on it for the dedicated coordinate system and a MeV-Green immobilizer was used for the patient setup by the help of side panels and plastic rods. By designing and constructing the whole body frame in this way, geometrical limitation to the gantry rotation in 3-D conformal radiotherapy could be minimized and problem which radiation transmission may be altered in particular incident angles was solved. By analyzing CT images containing information of patient setup with respect to the whole body frame, localization and coordination of the target is performed so that patient setup error may be eliminated between simulation and treatment. For the verification of setup, the change of patient positioning is detected and adjusted in order to minimize the setup error by means of comparison of the body outlines using 3 CCTV cameras. To enhance efficiency of treatment procedure, this work can be done in real time by watching the change of patient setup through the monitor. The method of image subtraction in IDL (Interactive Data Language) was used to visualize the change of patient setup. Rotating X-ray system was constructed for detecting target movement due to internal organ motion. Landmark screws were implanted either on the bones around target or inside target, and variation of target location with respect to markers may be visualized in order to minimize internal setup error through the anterior and the lateral image information taken from rotating X-ray system. For CT simulation, simulation software was developed using IDL on GUI(Graphic User Interface) basis for PC and includes functions of graphic handling, editing and data acquisition of images of internal organs as well as target for the preparation of treatment planning.

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