• 제목/요약/키워드: adaptive background

검색결과 343건 처리시간 0.028초

마커 은닉을 위한 패치 기반 텍스쳐 합성 (Patch-based Texture Synthesis for Marker Concealment)

  • 윤경담;우운택
    • 한국HCI학회논문지
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    • 제2권2호
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    • pp.11-18
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    • 2007
  • 본 논문은 영상의 자연스러운 증강을 위하여 패치 기반 텍스쳐 합성에 의한 마커 은닉 방법을 제안한다. 마커는 증강현실을 구성하는 물체의 인식과 추적을 위해 효과적인 도구로 활용되지만, 시각적으로 강조되어야 하는 특성으로 인해 증강현실의 실감성 감소와 사용성 저하를 유발한다는 문제점을 가지고 있다. 제안된 방법은 영상 속의 마커를 대체할 수 있도록 주변 배경과 어울리는 새로운 영상을 합성하여 마커를 은닉한다. 패치 기반의 텍스쳐 합성알고리즘을 사용하여 실시간성을 보장하는 동시에, 배경 텍스쳐의 전역적인 특성을 유지하고, 영상 주변의 조명 변화에 유연하다는 장점이 있다.

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Motion Compensated Subband Video Coding with Arbitrarily Shaped Region Adaptivity

  • Kwon, Oh-Jin;Choi, Seok-Rim
    • ETRI Journal
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    • 제23권4호
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    • pp.190-198
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    • 2001
  • The performance of Motion Compensated Discrete Cosine Transform (MC-DCT) video coding is improved by using the region adaptive subband image coding [18]. On the assumption that the video is acquired from the camera on a moving platform and the distance between the camera and the scene is large enough, both the motion of camera and the motion of moving objects in a frame are compensated. For the compensation of camera motion, a feature matching algorithm is employed. Several feature points extracted using a Sobel operator are used to compensate the camera motion of translation, rotation, and zoom. The illumination change between frames is also compensated. Motion compensated frame differences are divided into three regions called stationary background, moving objects, and newly emerging areas each of which is arbitrarily shaped. Different quantizers are used for different regions. Compared to the conventional MC-DCT video coding using block matching algorithm, our video coding scheme shows about 1.0-dB improvements on average for the experimental video samples.

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다수 차량의 후면 번호판 추출 (Rear Car License plate Detection of One More Cars)

  • 김영백;이상용
    • 제어로봇시스템학회논문지
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    • 제12권4호
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    • pp.400-404
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    • 2006
  • We suggest a method to detect rear car license plate of one more cars by using blobs. First, we try to search all of the blobs from an input image based on the difference between objects and background. Second, we obtain rectangles enclosed the blobs, and rectangle clusters by considering the properties, for example, the number, size, distance, position. Third, the cluster is verified by the Support Vector Machine. Even if we only use the adaptive binarization as the preprocessing, the detection ratio is very high.

A Study on the Detection Algorithm of an Advanced Ultrasonic Signal for Hydro-acoustic Releaser

  • Kim, Young-Jin;Huh, Kyung-Moo;Cho, Young-June
    • International Journal of Control, Automation, and Systems
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    • 제6권5호
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    • pp.767-775
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    • 2008
  • Methods used for exploring marine resources and spaces include positioning a probe under water and then recalling it after a specified time. Hydro-acoustic Releasers are commonly used for positioning and retrieving of such exploration equipment. The most important factor in this kind of system is the reliability for recalling the instruments. The frequently used ultrasonic signal detection method can detect ultrasonic signals using a fixed comparator, but because of increased rates of errors due to outside interferences, information is repetitively acquired. This study presents an effective ultrasonic signal detection algorithm using the characteristics of a resonance and adaptive comparator Combined with the FSK+ASK modulator. As a result, approximately 8.8% of ultrasonic wave communication errors caused by background noise and transmission losses were reduced for effectively detecting ultrasonic waves. Furthermore, the resonance circuit's quality factor was enhanced (Q = 120 to 160). As such, the bias voltage of the transistor (Vb= 3.3 to 6.8V) was increased thereby enhancing the frequency's selectivity.

골격 특징 및 색상 유사도를 이용한 가축 도난 감지 시스템 (Livestock Theft Detection System Using Skeleton Feature and Color Similarity)

  • 김준형;주영훈
    • 전기학회논문지
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    • 제67권4호
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    • pp.586-594
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    • 2018
  • In this paper, we propose a livestock theft detection system through moving object classification and tracking method. To do this, first, we extract moving objects using GMM(Gaussian Mixture Model) and RGB background modeling method. Second, it utilizes a morphology technique to remove shadows and noise, and recognizes moving objects through labeling. Third, the recognized moving objects are classified into human and livestock using skeletal features and color similarity judgment. Fourth, for the classified moving objects, CAM (Continuously Adaptive Meanshift) Shift and Kalman Filter are used to perform tracking and overlapping judgment, and risk is judged to generate a notification. Finally, several experiments demonstrate the feasibility and applicability of the proposed method.

Signal Recovery of the Corrupted Metal Impact Signal using the Adaptive Filtering in NPPs

  • Kim, Dai-Il;Shin, Won-Ky;Oh, Sung-Hun;Yun, Won-Young
    • 한국원자력학회:학술대회논문집
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    • 한국원자력학회 1995년도 추계학술발표회논문집(1)
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    • pp.223-229
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    • 1995
  • Loose Par Monitoring System(LPMS) is one of the fundamental diagnostic tools installed in the nuclear power plants. In this paper, recovery process algorithm and model for the corrupted impact signal generated by loose parts is presented. The characteristics of this algorithm can obtain a proper burst signal even though background noise is considerably high level comparing with actual impact signal. To verify performance of the proposed algorithm, we evaluate mathematically signal-to-noise ratio of primary output and noise. The performance of this recovery process algorithm is shown through computer simulation.

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Hand Gesture Recognition using Improved Hidden Markov Models

  • Xu, Wenkai;Lee, Eung-Joo
    • 한국멀티미디어학회논문지
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    • 제14권7호
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    • pp.866-871
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    • 2011
  • In this paper, an improved method of hand detecting and hand gesture recognition is proposed, it can be applied in different illumination condition and complex background. We use Adaptive Skin Threshold (AST) to detect the areas of hand. Then the result of hand detection is used to hand recognition through the improved HMM algorithm. At last, we design a simple program using the result of hand recognition for recognizing "stone, scissors, cloth" these three kinds of hand gesture. Experimental results had proved that the hand and gesture can be detected and recognized with high average recognition rate (92.41%) and better than some other methods such as syntactical analysis, neural based approach by using our approach.

Splitting and Merging Algorithm Based on Local Statistics of Sub-Regions in Document Image

  • Thapaliya, Kiran;Park, Il-Cheol;Kwon, Goo-Rak
    • Journal of information and communication convergence engineering
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    • 제9권5호
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    • pp.487-490
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    • 2011
  • This paper presents splitting and merging algorithm based on adaptive thresholding. The algorithm first divides the image into blocks, and then compares each block using the calculated thresholding value. The blocks which are same are merged using the certain threshold value and different blocks are split unless it satisfies the threshold value. When the block has been merged, maximum and minimum block sizes are determined then the average block size is determined. After the average block size is determined the average intensity and standard deviation of average block is calculated. The process of thresholding is applied to binarize the image. Finally, the experimental results show that the proposed method distinguishes clearly the background with text in the document image.

Feedback Active Noise Control Based Voice Enhancing Ear-Protection System

  • Moon, Seong-Pil;Chang, Tae-Gyu
    • Journal of Electrical Engineering and Technology
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    • 제12권4호
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    • pp.1627-1633
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    • 2017
  • This paper proposes a voice enhancing ear-protection system which is based on feedback active noise control(FBANC). The proposed system selectively suppresses the background noise and preserves the talking voice by controlling the adaptive algorithm with the voice activity period detection module. The noise reduction performance of the proposed noise canceling algorithm is analytically derived for the two key performance affecting parameters, i.e., electro-acoustic coupling distance and noise bandwidth. The proposed system is also implemented with a floating-point DSP system and its performance is experimentally tested to compare with the analytically derived results. The achieved levels of noise reduction for the three different noise bandwidths cases, i.e., 10Hz, 50Hz, and 90Hz, are high to show 17.05dB, 10.54dB and 8.99dB, respectively. The feasibility of the proposed system is also shown by the peak noise reduction achieved more than 25dB while preserving the voice component in the frequency range between 200-800Hz.

A Real-time Face Tracking Algorithm using Improved CamShift with Depth Information

  • Lee, Jun-Hwan;Jung, Hyun-jo;Yoo, Jisang
    • Journal of Electrical Engineering and Technology
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    • 제12권5호
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    • pp.2067-2078
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    • 2017
  • In this paper, a new face tracking algorithm is proposed. The CamShift (Continuously adaptive mean SHIFT) algorithm shows unstable tracking when there exist objects with similar color to that of face in the background. This drawback of the CamShift is resolved by the proposed algorithm using Kinect's pixel-by-pixel depth information and the skin detection method to extract candidate skin regions in HSV color space. Additionally, even when the target face is disappeared, or occluded, the proposed algorithm makes it robust to this occlusion by the feature point matching. Through experimental results, it is shown that the proposed algorithm is superior in tracking performance to that of existing TLD (Tracking-Learning-Detection) algorithm, and offers faster processing speed. Also, it overcomes all the existing shortfalls of CamShift with almost comparable processing time.