• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.20 no.4
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• pp.386-394
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• 2011

This paper is concerned with the application of the vision control scheme for robot's point placement task in discontinuous trajectory caused by obstacle. The proposed vision control scheme consists of four models, which are the robot's kinematic model, vision system model, 6-parameters estimation model, and robot's joint angles estimation model. For this study, the discontinuous trajectory by obstacle is divided into two obstacle regions. Each obstacle region consists of 3 cases, according to the variation of number of cameras that can not acquire the vision data. Then, the effects of number of cameras on the proposed robot's vision control scheme are investigated in each obstacle region. Finally, the practicality of the proposed robot's vision control scheme is demonstrated experimentally by performing the robot's point placement task in discontinuous trajectory by obstacle.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2012.07a
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• pp.262-265
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• 2012

In this paper we propose a new deinterlacing method with block classification and motion vector smoothing. The proposed method classifies a block, then depending on the region it belongs to, the motion estimation or line averaging is applied. To classify a block its variance is calculated. Then, for those blocks that belong to simple non-texture region the line averaging is done while motion estimation is applied to complex region. The motion vector field is smoothed using median filter what yields more accurate interpolation. In the experiments for the subjective evaluation, the proposed method bas shown satisfying results in terms of computation time consumption and peak signal-to-noise ratio. Due to the simplicity of the algorithm computation time was drastically decreased.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.8
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• pp.773-780
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• 2015

Navigation in outdoor environments is a fundamental and challenging problem for unmanned ground vehicles. Detecting lane markings or boundaries on the road may be one of the solutions to make navigation easy. However, because of various environments and road conditions, a robust lane detection is difficult. In this paper, we propose a new approach for estimating virtual lanes on a traversable region. Estimating the virtual lanes consist of two steps: (i) we detect virtual road region through road model selection based on traversability at current frame and similarity between the interframe and (ii) we estimate virtual lane using the number of lane on the road and results of previous frame. To improve the detection performance and reduce the searching region of interests, we use a probability map representing the traversability of the outdoor terrain. In addition, by considering both current and previous frame simultaneously, the proposed method estimate more stable virtual lanes. We evaluate the performance of the proposed approach using real data in outdoor environments.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2006.05a
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• pp.397-401
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• 2006

In this paper, we proposed a high precision location estimation algorithm using an enhanced decision scheme for RTLS and analyzed its performance in point of an average estimation error distance at 2D coordinates searching area, $300m\times300m$ and LOS propagation environments. Also the performance was compared with that of conventional TDOA algorithm according to the number of available reader and received sub-blink. From the results, we confirmed that the proposed location estimation algorithm using an enhanced decision scheme was able to improve an estimation accuracy even in boundary region of searching area. Moreover, effectively reduced an error distance in entire searching area so that increased the stability of location estimation in RTLS. Therefore, we verified that the proposed algorithm provided a more higher estimation accuracy and stability than conventional TDOA.

• Journal of Korea Society of Digital Industry and Information Management
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• v.8 no.4
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• pp.13-18
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• 2012

In this paper, we propose a noise estimation method for noise reduction. It is based on block and pixel-based noise estimation. We assume that an input image is contaminated by the additive white Gaussian noise. Thus, we use an adaptive Gaussian filter and estimate the amount of noise. It computes the standard deviation of each block and estimation is performed on pixel-based operation. The proposed algorithm divides an input image into blocks. This method calculates the standard deviation of each block and finds the minimum standard deviation block. The block in flat region shows well noise and filtering effects. Blocks which have similar standard deviation are selected as test blocks. These pixels are filtered by adaptive Gaussian filtering. Then, the amount of noise is calculated by the standard deviation of the differences between noisy and filtered blocks. Experimental results show that our proposed estimation method has better results than those by existing estimation methods.

• Journal of Korea Multimedia Society
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• v.19 no.2
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• pp.240-251
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• 2016

This paper presents a real-time indoor location and pose estimation method that utilizes simple artificial markers and image analysis techniques for the purpose of warehouse automation. The conventional indoor localization methods cannot work robustly in warehouses where severe environmental changes usually occur due to the movement of stocked goods. To overcome this problem, the proposed framework places artificial markers having different interior pattern on the predefined position of the warehouse floor. The proposed algorithm obtains marker candidate regions from a captured image by a simple binarization and labeling procedure. Then it extracts maker interior pattern information from each candidate region in order to decide whether the candidate region is a true marker or not. The extracted interior pattern information and the outer boundary of the marker are used to estimate location and heading angle of the localization system. Experimental results show that the proposed localization method can provide high performance which is almost equivalent to that of the conventional method using an expensive LIDAR sensor and AMCL algorithm.

• Journal of Korea Multimedia Society
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• v.6 no.7
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• pp.1121-1130
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• 2003

This paper proposes a new motion estimation algorithm using the temporal continuity of motion. We set up a wide global search region (GSR), which basically corresponds to the search region of FSA, and local search regions (LSRs), the positions for which are predicted by the motion vectors of the temporal neighbor blocks, are constructed in the GSR. The previous frame blocks that possibly have effects on the current block are to be the temporal neighbor blocks. Then Motion estimation is only performed in the areas made by LSRs. Experimental results show that the proposed method can maintain visual qualifies with significant reductions of complexity by reducing search regions, when compared to the conventional FSA.

• Journal of Korea Multimedia Society
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• v.7 no.8
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• pp.1025-1034
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• 2004

This paper proposes an adaptive motion estimation algorithm using the temporal continuity of motion. We set up a squared global search region (GSR), which basically corresponds to the search region of FSA, and non-squared adaptive local search regions (LSRs), the positions for which are predicted by the motion vectors of the temporal neighbor blocks, are constructed in the GSR. The previous frame blocks that possibly have effects on the current block are to be the temporal neighbor blocks. Because motion estimation is only performed in the areas made by LSRs, we can estimate motion more correctly and reduce processing time. Experimental results show that the proposed method can enhance visual qualities with significant reductions of complexity by reducing search regions, when compared to the conventional methods.

• The Transactions of the Korean Institute of Electrical Engineers B
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• v.53 no.9
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• pp.552-561
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• 2004

This paper is concerned with a new speed sensorless induction motor scheme which can be successfully applied to at any speed including even zero speed. The proposed method is robust against rotor resistance variations. In addition, simultaneous on-line estimations of speed and rotor resistance are realized based on a feedforward type torque control approach. The rotor flux with a low frequency sinusoidal waveform has been utilized to help the simultaneous estimation for both speed and rotor resistance. The control scheme has no current minor loop to determine voltage references. Since the proposed estimation does not depend on any derivative terms of currents and stator voltages, it offers a good performance at extremely low speed region for sensorless induction motor. Furthermore, the proposed control is simply using motor parameters and stator currents without determining any PI gains for current feedback and any signal injection for the rotor resistance estimation. Finally, both simulation and experimental results are given to show the effectiveness of this method.

• The Korean Journal of Applied Statistics
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• v.13 no.2
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• pp.353-369
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• 2000

We systematized an stratified spatial sample design(SSSD) that uses the adequate stratification criteria such as the shapeness or the dispersion of an interesting region in a spatial population. And we proposed an adaptive searching estimation method in the SSSD to estimate the area of region of interest in two-dimensional surfaces. When wc adopt the proposed adaptive searching estimation method in SSSD, the observing sample size is more decreased than a classical sample design that all the designed sample size is observed. Nevertheless it has been shown that we can produce the moderate result but the efficiency is a slight reduced.