• Title/Summary/Keyword: adaptive background

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Adaptive Automatic Thresholding in Infrared Image Target Tracking (적외선 영상 표적추적 성능 개선을 위한 적응적인 자동문턱치 산출 기법 연구)

  • Kim, Tae-Han;Song, Taek-Lyul
    • Journal of Institute of Control, Robotics and Systems
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    • v.17 no.6
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    • pp.579-586
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    • 2011
  • It is very critical for image processing of IIR (Imaging Infrared) seekers to achieve improved guidance performance for missile systems to determine appropriate thresholds in various environments. In this paper, we propose automatic threshold determination methods for proper thresholds to extract definite target signals in an EOCM (Electro-Optical Countermeasures) environment with low SNR (Signal-to-Noise Ratios). In particular, thresholds are found to be too low to extract target signals if one uses the Otsu method so that we suggest a Shifted Otsu method to solve this problem. Also we improve extracting target signal by changing Shifted Otsu thresholds according to the TBR (Target to Background Ratio). The suggested method is tested for real IIR images and the results are compared with the Otsu method. The HPDAF (Highest Probabilistic Data Association Filter) which selects the target originated measurements by taking into account of both signal intensity and statistical distance information is applied in this study.

Adaptive Digital Watermarking with Perceptually Tuned Characteristic Based on Wavelet Transform (웨이브릿 변환영역에서 지각적 동조특성을 갖는 적응적 디지털 워터마킹)

  • 김현천;장봉주;서용수;김종진
    • Journal of Korea Multimedia Society
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    • v.6 no.6
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    • pp.1008-1014
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    • 2003
  • In this paper, we propose the image retrieval method based on object regions using bidirectional round filter in the wavelet transform domain. A conventional method that includes unnecessary background information reduce retrieval efficiency, because of the extraction of feature vectors from the whole region of subband. On proposed method, it extracts accurate feature vectors and keep certainly retrieval efficiency in case of reduced feature vectors, because of the extraction of feature vectors from the only extracted object region. Furthermore, it improve retrieval efficiency by removing unnecessary background information. Consequently, the retrieval efficiency is improved with 2.5%∼5.5% values, which have a little chances to vary according to characteristics of image.

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Stereo object Tracking System using Block Matching Algorithm and optical JTC (블록정합 알고리즘과 광 JTC를 이용한 스테레오 물체추적 시스템)

  • 이재수;이용범;김은수
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.25 no.3B
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    • pp.549-556
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    • 2000
  • In this paper, we propose a new adaptive stereo object tracking system that can be used when the back ground image is complex and the cameras are not fixed . In this method, we used the Block Matching Algorithm to separate the tracking object form the background image and then the optical JTC system is used to obtain the convergence-controlling and pa/tilt-controlling values fro the left and right cameras. the experimental results are found to track the object robustly & adaptively for the object tracking in various background images, and the possibility of real-time implementation of the proposed system by using the optical JTC is also suggested.

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Adaptive Medical Image Compression Based on Lossy and Lossless Embedded Zerotree Methods

  • Elhannachi, Sid Ahmed;Benamrane, Nacera;Abdelmalik, Taleb-Ahmed
    • Journal of Information Processing Systems
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    • v.13 no.1
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    • pp.40-56
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    • 2017
  • Since the progress of digital medical imaging techniques, it has been needed to compress the variety of medical images. In medical imaging, reversible compression of image's region of interest (ROI) which is diagnostically relevant is considered essential. Then, improving the global compression rate of the image can also be obtained by separately coding the ROI part and the remaining image (called background). For this purpose, the present work proposes an efficient reversible discrete cosine transform (RDCT) based embedded image coder designed for lossless ROI coding in very high compression ratio. Motivated by the wavelet structure of DCT, the proposed rearranged structure is well coupled with a lossless embedded zerotree wavelet coder (LEZW), while the background is highly compressed using the set partitioning in hierarchical trees (SPIHT) technique. Results coding shows that the performance of the proposed new coder is much superior to that of various state-of-art still image compression methods.

Adaptive Background Modeling Considering Stationary Object and Object Detection Technique based on Multiple Gaussian Distribution

  • Jeong, Jongmyeon;Choi, Jiyun
    • Journal of the Korea Society of Computer and Information
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    • v.23 no.11
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    • pp.51-57
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    • 2018
  • In this paper, we studied about the extraction of the parameter and implementation of speechreading system to recognize the Korean 8 vowel. Face features are detected by amplifying, reducing the image value and making a comparison between the image value which is represented for various value in various color space. The eyes position, the nose position, the inner boundary of lip, the outer boundary of upper lip and the outer line of the tooth is found to the feature and using the analysis the area of inner lip, the hight and width of inner lip, the outer line length of the tooth rate about a inner mouth area and the distance between the nose and outer boundary of upper lip are used for the parameter. 2400 data are gathered and analyzed. Based on this analysis, the neural net is constructed and the recognition experiments are performed. In the experiment, 5 normal persons were sampled. The observational error between samples was corrected using normalization method. The experiment show very encouraging result about the usefulness of the parameter.

Stop Object Method within Intersection with Using Adaptive Background Image (적응적 배경영상을 이용한 교차로 내 정지 객체 검출 방법)

  • Kang, Sung-Jun;Sur, Am-Seog;Jeong, Sung-Hwan
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.14 no.5
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    • pp.2430-2436
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    • 2013
  • This study suggests a method of detecting the still object, which becomes a cause of danger within the crossroad. The Inverse Perspective Transform was performed in order to make the object size consistent by being inputted the real-time image from CCTV that is installed within the crossroad. It established the detection area in the image with the perspective transform and generated the adaptative background image with the use of the moving information on object. The detection of the stop object was detected the candidate region of the stop object by using the background-image differential method. To grasp the appearance of truth on the detected candidate region, a method is proposed that uses the gradient information on image and EHD(Edge Histogram Descriptor). To examine performance of the suggested algorithm, it experimented by storing the images in the commuting time and the daytime through DVR, which is installed on the cross street. As a result of experiment, it could efficiently detect the stop vehicle within the detection region inside the crossroad. The processing speed is shown in 13~18 frame per second according to the area of the detection region, thereby being judged to likely have no problem about the real-time processing.

Improved Mean-Shift Tracking using Adoptive Mixture of Hue and Saturation (색상과 채도의 적응적 조합을 이용한 개선된 Mean-Shift 추적)

  • Park, Han-dong;Oh, Jeong-su
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.19 no.10
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    • pp.2417-2422
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    • 2015
  • Mean-Shift tracking using hue has a problem that it fail in the object tracking when background has similar hue to the object. This paper proposes an improved Mean-Shift tracking algorithm using new data instead of a hue. The new data is generated by adaptive mixture of hue and saturation which have low interrelationship . That is, the proposed algorithm selects a main attribute of color that is able to distinguish the object and background well and a secondary one which don't, and places their upper 4 bits on upper 4 bits and lower 4 bits on the mixture data, respectively. The proposed algorithm properly tracks the object, keeping tracking error maximum 2.0~4.2 pixel and average 0.49~1.82 pixel, by selecting the saturation as the main attribute of color under tracking environment that background has similar hue to the object.

An Effective Shadow Elimination Method Using Adaptive Parameters Update (적응적 매개변수 갱신을 통한 효과적인 그림자 제거 기법)

  • Kim, Byeoung-Su;Lee, Gwang-Gook;Yoon, Ja-Young;Kim, Jae-Jun;Kim, Whoi-Yul
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.45 no.3
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    • pp.11-19
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    • 2008
  • Background subtraction, which separates moving objects in video sequences, is an essential technology for object recognition and tracking. However, background subtraction methods are often confused by shadow regions and this misclassification of shadow regions disturbs further processes to perceive the shapes or exact positions of moving objects. This paper proposes a method for shadow elimination which is based on shadow modeling by color information and Bayesian classification framework. Also, because of dynamic update of modeling parametres, the proposed method is able to correspond adaptively to illumination changes. Experimental results proved that the proposed method can eliminate shadow regions effectively even for circumstances with varying lighting condition.

Real-Time Head Tracking using Adaptive Boosting in Surveillance (서베일런스에서 Adaptive Boosting을 이용한 실시간 헤드 트래킹)

  • Kang, Sung-Kwan;Lee, Jung-Hyun
    • Journal of Digital Convergence
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    • v.11 no.2
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    • pp.243-248
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    • 2013
  • This paper proposes an effective method using Adaptive Boosting to track a person's head in complex background. By only one way to feature extraction methods are not sufficient for modeling a person's head. Therefore, the method proposed in this paper, several feature extraction methods for the accuracy of the detection head running at the same time. Feature Extraction for the imaging of the head was extracted using sub-region and Haar wavelet transform. Sub-region represents the local characteristics of the head, Haar wavelet transform can indicate the frequency characteristics of face. Therefore, if we use them to extract the features of face, effective modeling is possible. In the proposed method to track down the man's head from the input video in real time, we ues the results after learning Harr-wavelet characteristics of the three types using AdaBoosting algorithm. Originally the AdaBoosting algorithm, there is a very long learning time, if learning data was changes, and then it is need to be performed learning again. In order to overcome this shortcoming, in this research propose efficient method using cascade AdaBoosting. This method reduces the learning time for the imaging of the head, and can respond effectively to changes in the learning data. The proposed method generated classifier with excellent performance using less learning time and learning data. In addition, this method accurately detect and track head of person from a variety of head data in real-time video images.

Adaptive Re-reflecting Wave Control in Plunger Type Wave Maker System: Theory

  • Park, Jae-Woong;Lee, Jin-Ho;Park, Gun-Il;Kim, Ki-Jung
    • Journal of Ship and Ocean Technology
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    • v.6 no.4
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    • pp.13-18
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    • 2002
  • Active control has been partly applied to suppress the re-reflecting waves in wave basin with plunger-type wave maker to obtain desirable waves. This limitation comes from the non-confirmable theoretical background to the control algorithm. This paper proposes control logic to overcome this drawback, based on the impulse response function for propagating waves between control input and the wave height. The performances have been verified as reasonable in practical application by comparing with the propagating wave components in numerical wave basin, using wave decomposition method. Moreover, the control logic can also give useful wave-absorbing performance after cessation of wave generation.