• Title/Summary/Keyword: 적응 임계값

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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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Accuracy Improvement Methode of Step Count Detection Using Variable Amplitude Threshold (가변 진폭 임계값을 이용한 걸음수 검출 정확도 향상 기법)

  • Ryu, Uk Jae;Kim, En Tae;An, Kyung Ho;Chang, Yun Seok
    • KIPS Transactions on Computer and Communication Systems
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    • v.2 no.6
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    • pp.257-264
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    • 2013
  • In this study, we have designed the variable amplitude threshold algorithm that can enhance the accuracy of step count using variable amplitude. This algorithm converts the x, y, z sensor values into a single energy value($E_t$) by using SVM(Signal Vector Magnitude) algorithm and can pick step count out over 99% of accuracy through the peak data detection algorithm and fixed peak threshold. To prove the results, We made the noise filtering with the fixed amplitude threshold from the amplitude of energy value that found out the detection error was increasing, and it's the key idea of the variable amplitude threshold that can be adapted on the continuous data evaluation. The experiment results shows that the variable amplitude threshold algorithm can improve the average step count accuracy up to 98.9% at 10 Hz sampling rate and 99.6% at 20Hz sampling rate.

Local-property aware masking method on hardware implementation (국부특성을 반영한 하드웨어 기반의 마스킹 방식)

  • 정영훈
    • Proceedings of the Korea Multimedia Society Conference
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    • 2003.11a
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    • pp.220-223
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    • 2003
  • 이진 출력 기기에서 연속 계조의 영상을 받아들여 이진값으로 출력하는 이진화 알고리즘 중한 예로 마스킹(masking) 방법이 있으며, 마스크 방식의 단점을 보완하였다. 동일한 마스크의 반복적인 사용으로 인하여 영상의 부분적인 특성을 잘 표현해 주지 못하는 마스크들의 단정을 보완하기 위해서 국부 적응 임계값과 테이블 방식의 적응 파라메타를 제안하였으며, 결과적으로 시각적으로 중요한 경계성분을 강조와 국부 처리시 계조 표현력이 부족한 배경영역도 충분히 표현할 수 있었다.

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Adaptive morphological Wavelet-CNN Algorithm for the Color Image Edge detection (컬러 영상 에지 검출을 위한 적응 형태학적 WCNN 알고리즘)

  • Beak, Young-Hyun;Moon, Sung-Rung
    • Journal of the Korean Institute of Intelligent Systems
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    • v.14 no.4
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    • pp.473-480
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    • 2004
  • This paper presents a new edge detection algorithm in color image. The proposed Adaptive morphological Wavelet-CNN algorithm is divided into two parts : The Adaptive morpholog and WCNN(Wavelet Cellular Neural Networks). It detects the optimal edge with applying this color image to WCNN algorithm, after it does level up a boundary side of a color image by using the adaptive morphology as the threshold of an input color image. Also, it is used not a conventional fixed mask edge detection method but variable mask method which is called a variable BBM. Finally, to show the feasibility of the proposed algorithm, this paper provides by simulation that the color image consists of 30.

Algorithm for Intelligent Control to Prevent Over Estimation in Fast Adaptive Perceptual Filter (고속 적응 지각 필터에서 잡음 과추정 방지를 위한 지능적 제어 알고리즘)

  • Ryu Il-Hyun;Koo Kyo-Sik;Cha Hyung-Tai
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 2005.04a
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    • pp.437-440
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    • 2005
  • 본 논문에서는 고속의 적웅 지각 필터에서 잡음 과추정으로 인해서 발생하는 불필요한 반복 계산 및 결과 신호의 SNR 성능 저하를 개선시키는 방법을 제안한다. 적응 지각 필터를 고속연산이 가능하도록 개선하는 과정에서 시간적인 측면에서는 많은 성능의 개선이 있었지만 음질 개선 과정에서 과추정된 잡음의 적용에 의한 성능 저하가 발생하였다. 제안하는 시스템에서는 적웅 지각 필터의 임계값을 조정하고, 임계값이외에 발생하는 잡음 과추정에 대해서 실험적으로 필터 반복 연산량 제한을 통해 향상된 결과를 얻었다. 이 시스템에서 필터 반복 연산량은 입력 구간의 신호에 따라 적응적으로 제한된다. 제안된 알고리즘의 개선 확인을 위해서 감소된 반복 연산량과 SNR 개선량을 측정하여 기존의 방법과 비교하였다.

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Shot Change Detection Technique Using Adaptive Threshold Setting Method on Variable Reference Block and Implementation on PMP (가변 참조 구간에서의 적응적 임계값 설정 방법을 이용한 장면 전환 검출 기술과 PMP에서의 구현)

  • Kim, Won-Hee;Moon, Kwang-Seok;Kim, Jong-Nam
    • Journal of Korea Multimedia Society
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    • v.12 no.3
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    • pp.354-361
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    • 2009
  • Shot change detection is the main technique in the video segmentation which requirs real-time processing and automatical processing in hardware. Until now, there were few research reports about real-time shot change detection for applying to hardware terminals with low performance such as PMPs(Portable Media Player) and cellular phones. In this paper, we propose shot change detection technique using adaptive threshold setting method on variable reference block. Our proposed algorithm determines shot change detection by comparing the feature value of current frame and a mean of a feature value on variable reference blocks. The proposed method can be used independently from the feature value of frame, can adaptively set thresholds using a mean of a feature value on variable reference blocks. We obtained better detection ratio than the conventional methods maximally by precision 0.146, recall 0.083, F1 0.089 in the experiment with the same test sequences. We verified real-time operation of shot change detection by implementing our algorithm on the PMP from some company of H. Therefore, our proposing algorithm will be helpful in searching video data on portable media players such as PMPs and cellular phones.

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Obtaining Object by Using Optimal Threshold for Saliency Map Thresholding (Saliency Map을 이용한 최적 임계값 기반의 객체 추출)

  • Hai, Nguyen Cao Truong;Kim, Do-Yeon;Park, Hyuk-Ro
    • The Journal of the Korea Contents Association
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    • v.11 no.6
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    • pp.18-25
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    • 2011
  • Salient object attracts more and more attention from researchers due to its important role in many fields of multimedia processing like tracking, segmentation, adaptive compression, and content-base image retrieval. Usually, a saliency map is binarized into black and white map, which is considered as the binary mask of the salient object in the image. Still, the threshold is heuristically chosen or parametrically controlled. This paper suggests using the global optimal threshold to perform saliency map thresholding. This work also considers the usage of multi-level optimal thresholds and the local adaptive thresholds in the experiments. These experimental results show that using global optimal threshold method is better than parametric controlled or local adaptive threshold method.

Real-Time Step Count Detection Algorithm Using a Tri-Axial Accelerometer (3축 가속도 센서를 이용한 실시간 걸음 수 검출 알고리즘)

  • Kim, Yun-Kyung;Kim, Sung-Mok;Lho, Hyung-Suk;Cho, We-Duke
    • Journal of Internet Computing and Services
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    • v.12 no.3
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    • pp.17-26
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    • 2011
  • We have developed a wearable device that can convert sensor data into real-time step counts. Sensor data on gait were acquired using a triaxial accelerometer. A test was performed according to a test protocol for different walking speeds, e.g., slow walking, walking, fast walking, slow running, running, and fast running. Each test was carried out for 36 min on a treadmill with the participant wearing an Actical device, and the device developed in this study. The signal vector magnitude (SVM) was used to process the X, Y, and Z values output by the triaxial accelerometer into one representative value. In addition, for accurate step-count detection, we used three algorithms: an heuristic algorithm (HA), the adaptive threshold algorithm (ATA), and the adaptive locking period algorithm (ALPA). The recognition rate of our algorithm was 97.34% better than that of the Actical device(91.74%) by 5.6%.

A Robust Marker Detection Algorithm Using Hybrid Features in Augmented Reality (증강현실 환경에서 복합특징 기반의 강인한 마커 검출 알고리즘)

  • Park, Gyu-Ho;Lee, Heng-Suk;Han, Kyu-Phil
    • The KIPS Transactions:PartA
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    • v.17A no.4
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    • pp.189-196
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    • 2010
  • This paper presents an improved marker detection algorithm using hybrid features such as corner, line segment, region, and adaptive threshold values, etc. In usual augmented reality environments, there are often marker occlusion and poor illumination. However, existing ARToolkit fails to recognize the marker in these situations, especially, partial concealment of marker by user, large change of illumination and dim circumstances. In order to solve these problems, the adaptive threshold technique is adopted to extract a marker region and a corner extraction method based on line segments is presented against marker occlusions. In addition, a compensating method, corresponding the marker size and center between registered and extracted one, is proposed to increase the template matching efficiency, because the inside marker size of warped images is slightly distorted due to the movement of corner and warping. Therefore, experimental results showed that the proposed algorithm can robustly detect the marker in severe illumination change and occlusion environment and use similar markers because the matching efficiency was increased almost 30%.