• Title/Summary/Keyword: Motion compensation error

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Modified Swimming Pattern to Control Propulsive Force for Biomimetic Underwater Articulated Robot (생체모방형 수중 다관절 로봇의 추진력 제어를 위한 유영 패턴 재생성)

  • Jeong, Seonghwan;Lee, Jihong
    • The Journal of Korea Robotics Society
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    • v.11 no.4
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    • pp.285-292
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    • 2016
  • For articulated swimming robots, there have been no researches about controlling the motion or trajectory following. A control method for articulated swimming robot is suggested by extending a previous algorithm, ESPG (Extended Swimming Pattern Generator). The control method focuses on the situation that continuous pre-determined swimming pattern is applied for long range travelling. In previous studies, there has not been a way to control the propulsive force when a swimming pattern created by ESPG was in progress. Hence, no control could be made unless the swimming pattern was completed even though an error occurred while the swimming pattern was in progress. In order to solve this problem, this study analyzes swimming patterns and suggests a method to control the propulsive force even while the swimming pattern was in progress. The angular velocity of each link is influenced and this eventually modifies the propulsive force. However, The angular velocity is changed, a number of problems can occur. In order to resolve this issue, phase compensation method and synchronization method were suggested. A simple controller was designed to confirm whether the suggested methods are able to control and a simulation has affirmed it. Moreover, it was applied to CALEB 10 (a biomimetic underwater articulated robot) and the result was verified.

Low Complexity Video Encoding Using Turbo Decoding Error Concealments for Sensor Network Application (센서네트워크상의 응용을 위한 터보 복호화 오류정정 기법을 이용한 경량화 비디오 부호화 방법)

  • Ko, Bong-Hyuck;Shim, Hyuk-Jae;Jeon, Byeung-Woo
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.45 no.1
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    • pp.11-21
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    • 2008
  • In conventional video coding, the complexity of encoder is much higher than that of decoder. However, as more needs arises for extremely simple encoder in environments having constrained energy such as sensor network, much investigation has been carried out for eliminating motion prediction/compensation claiming most complexity and energy in encoder. The Wyner-Ziv coding, one of the representative schemes for the problem, reconstructs video at decoder by correcting noise on side information using channel coding technique such as turbo code. Since the encoder generates only parity bits without performing any type of processes extracting correlation information between frames, it has an extremely simple structure. However, turbo decoding errors occur in noisy side information. When there are high-motion or occlusion between frames, more turbo decoding errors appear in reconstructed frame and look like Salt & Pepper noise. This severely deteriorates subjective video quality even though such noise rarely occurs. In this paper, we propose a computationally extremely light encoder based on symbol-level Wyner-Ziv coding technique and a new corresponding decoder which, based on a decision whether a pixel has error or not, applies median filter selectively in order to minimize loss of texture detail from filtering. The proposed method claims extremely low encoder complexity and shows improvements both in subjective quality and PSNR. Our experiments have verified average PSNR gain of up to 0.8dB.

Investigation of Sensor Models for Precise Geolocation of GOES-9 Images (GOES-9 영상의 정밀기하보정을 위한 여러 센서모델 분석)

  • Hur, Dong-Seok;Kim, Tae-Jung
    • Korean Journal of Remote Sensing
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    • v.22 no.4
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    • pp.285-294
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    • 2006
  • A numerical formula that presents relationship between a point of a satellite image and its ground position is called a sensor model. For precise geolocation of satellite images, we need an error-free sensor model. However, the sensor model based on GOES ephemeris data has some error, in particular after Image Motion Compensation (IMC) mechanism has been turned off. To solve this problem, we investigated three sensor models: collinearity model, direct linear transform (DLT) model and orbit-based model. We applied matching between GOES images and global coastline database and used successful results as control points. With control points we improved the initial image geolocation accuracy using the three models. We compared results from three sensor models. As a result, we showed that the orbit-based model is a suitable sensor model for precise geolocation of GOES-9 Images.

Lightweight video coding using spatial correlation and symbol-level error-correction channel code (공간적 유사성과 심볼단위 오류정정 채널 코드를 이용한 경량화 비디오 부호화 방법)

  • Ko, Bong-Hyuck;Shim, Hiuk-Jae;Jeon, Byeung-Woo
    • Journal of Broadcast Engineering
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    • v.13 no.2
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    • pp.188-199
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    • 2008
  • In conventional video coding, encoder complexity is much higher than that of decoder. However, investigations for lightweight encoder to eliminate motion prediction/compensation claiming most complexity in encoder have recently become an important issue. The Wyner-Ziv coding is one of the representative schemes for the problem and, in this scheme, since encoder generates only parity bits of a current frame without performing any type of processes extracting correlation information between frames, it has an extremely simple structure compared to conventional coding techniques. However, in Wyner-Ziv coding, channel decoding errors occur when noisy side information is used in channel decoding process. These channel decoding errors appear more frequently, especially, when there is not enough correlation between frames to generate accurate side information and, as a result, those errors look like Salt & Pepper type noise in the reconstructed frame. Since this noise severely deteriorates subjective video quality even though such noise rarely occurs, previously we proposed a computationally extremely light encoding method based on selective median filter that corrects such noise using spatial correlation of a frame. However, in the previous method, there is a problem that loss of texture from filtering may exceed gain from error correction by the filter for video sequences having complex torture. Therefore, in this paper, we propose an improved lightweight encoding method that minimizes loss of texture detail from filtering by allowing information of texture and that of noise in side information to be utilized by the selective median filter. Our experiments have verified average PSNR gain of up to 0.84dB compared to the previous method.

Intensity Correction of 3D Stereoscopic Images Using Binarization-Based Region Segmentation (이진화기반 영역분할을 이용한 3D입체영상의 밝기보정)

  • Kim, Sang-Hyun;Kim, Jeong-Yeop
    • The KIPS Transactions:PartB
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    • v.18B no.5
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    • pp.265-270
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    • 2011
  • In this paper, we propose a method for intensity correction using binarization-based region segmentation in 3D stereoscopic images. In the proposed method, 3D stereoscopic right image is segmented using binarizarion. Small regions in the segmented image are eliminated. For each region in right image, a corresponding region in left image is decided through region matching using correlation coefficient. When region-based matching, in order to prevent overlap between regions, we remove a portion of the area closed to the region boundary using morphological filter. The intensity correction in left and right image can be performed through histogram specification between the corresponding regions. Simulation results show the proposed method has the smallest matching error than the conventional method when we generate the right image from the left image using block based motion compensation.