• Tunnel and Underground Space
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• v.4 no.3
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• pp.274-286
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• 1994

Direct shear tests were on ducted in a laboratory setting in order to investigate the shear strength and deformation behavior of rock joints. Also, the characteristics of acoustic emissions (AE) during shearing of rock joints were studied. The artificial rock joints were created by splitting the intact blocks of Hwangdeung granites and Iksan marbles. Joint roughness profiles were measured by a profile gage and then digitized by Image analyzer. Roughness profile indices(Rp) of the joints were calculated with these digitized data. Peak shear strength, residual shear strength, shear stiffness and maximum acoustic emission(AE) rate were investigated with joint roughness. The peak shear strenght, the residual shear strength and the shear stiffness were increased as roughness popfile index or normal stress increased in the shear tests of granites. In the tests of marble samples, the shear deformation characteristics were not directly affected by joint roughness. As the result of two directional shear tests, the shear characteristics were varied with shear direction. AE count rates were measured during the shear deformation and the AE signals in several stages of the deformation were analyzed in a frequency domain. The AE rate peaks coincided with the stress drops during the shear deformation of joint. The dominant frequencies of the AE signals were in the vicinity of 100 kHz fo rgranite sample and 900 kHz for marble samples. The distribution of amplitude was dispersed with increasing normal stress.

• International Journal of Aeronautical and Space Sciences
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• v.14 no.3
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• pp.282-295
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• 2013

In order to communicate with a ground station, the tracking profile design problem for a directional antenna system is considered. Because the motions of the gimbal angles in the antenna system affect the image quality, the main object is to minimize the motion of the gimbal angles during the satellite's imaging phase. For this goal, parameter optimization problems in the imaging and maneuver phases are formulated separately in the body-frame, and solved sequentially. Also, several mechanical constraints, such as the limitation of the gimbal angle and rate, are considered in the problems. The tracking profiles of the gimbal angles in the maneuver phases are designed with N-th order polynomials, to continuously connect the tracking profiles between two imaging phases. The results confirm that if the vector trace of the desired antenna-pointing vector is within the antenna's beam-width angle, motions of the gimbal angles are not required in the corresponding imaging phase. Also, through numerical examples, it is shown that motion of the gimbal angles in the imaging phase can be minimized by the proposed design process.

• Journal of Institute of Control, Robotics and Systems
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• v.11 no.5
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• pp.423-428
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• 2005

This paper proposes a new edge detection method using a $3{\times}3$ ideal binary pattern and lookup table (LUT) for the mobile robot localization without any parameter adjustments. We take the mean of the pixels within the $3{\times}3$ block as a threshold by which the pixels are divided into two groups. The edge magnitude and orientation are calculated by taking the difference of average intensities of the two groups and by searching directional code in the LUT, respectively. And also the input image is not only partitioned into multiple groups according to their intensity similarities by the histogram, but also the threshold of each group is determined by fuzzy reasoning automatically. Finally, the edges are determined through non-maximum suppression using edge confidence measure and edge linking. Applying this edge detection method to the mobile robot localization using projective invariance of the cross ratio. we demonstrate the robustness of the proposed method to the illumination changes in a corridor environment.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.29B no.10
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• pp.69-77
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• 1992

Pattern Recognition is one of the fundamental areas of computer vision. The recognition of patterns with varying size and severe defects is especially important. However, it is known that the conventional algorithms such as GHT or structural approaches have limitations in speed and accuracy. In this paper, in order to avoid above-mentioned problems, we propose a new recognition algorithm which exploits the histogram of contour directions and the sampled spot matching method. While the former provides little influence against size variation, the latter has strong immunity to noise and defects. We applied those proposed algorithms for the recognition of numbers extracted from the car number plates and shapes of aircraft. Experimental result shows that it is possible to solve above-mentioned problems by complementary uses of those two suggested algorithms. The contour directional histogram method resulted in high-speed of average 0.013 sec/char and 0.1 sec/aircraft-image on IBM-386. The accuracy of recognition is as high as 99%. Sampled spot matching method has less speed than the former one, however, it showed fairly strong immunity to noise and defects.

• Proceedings of the KSRS Conference
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• 2002.10a
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• pp.235-240
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• 2002

This paper shows the desist concept of an ATS(Antenna Tracking Software) to control the movement of the MSC(Multi-Spectral Camera) antenna. The MSC has a two-axes directional X-band antenna for image transmission to KGS(KOMSAT2 Ground Station). The main objective of the ATS is to drive the APM(Antenna Pointing Mechanism) to the required elevation and the azimuth position according to an appropriate TPF(Tracking Parameter File). The ATS is implemented as one task of the SBC(Single Board Computer) software, which uses VxWorks as a real time OS. The ATS has several operational modes such as STANDBY mode, First EL mode, First AZ mode, Normal Operation mode, and so on. The ATS uses two PI controllers fur the velocity and the position loop respectively, to satisfy the requirements specification. In order to show the feasibility of the described design concept, the various simulations and the experiments are performed under specific test configuration.

• Nuclear Engineering and Technology
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• v.54 no.6
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• pp.1982-1990
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• 2022

The purpose of this study was to verify the possibility of fuel rod pattern analysis in a fresh fuel assembly using the Yonsei single-photon emission computed tomography (YSECT) system. The YSECT system consisted of three main parts: four trapezoidal-shaped bismuth germanate scintillator-based 64-channel detectors, a semiconductor-based multi-channel data acquisition system, and a rotary stage. In order to assess the performance of the prototype YSECT, tomographic images were obtained for three representative fuel rod patterns in the 6 × 6 array using two representative image-reconstruction algorithms. The fuel-rod patterns were then assessed using an in-house fuel rod pattern analysis algorithm. In the experimental results, the single-directional projection images for those three fuel-rod patterns well discriminated each fuel-rod location, showing a Gaussian-peak-shaped projection for a single 10 mm-diameter fuel rod with 12.1 mm full-width at half maximum. Finally, we successfully verified the possibility of the fuel rod pattern analysis for all three patterns of fresh fuel rods with the tomographic images obtained by the rotational YSECT system.

• Proceedings of the Korea Information Processing Society Conference
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• 2023.05a
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• pp.615-617
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• 2023

In recent years, the growing popularity of dogs due to the benefits they bring their owners has contributed to the increase of the number of dogs raised. For owners, it is their responsibility to ensure their dogs' health and safety. However, it is challenging for them to continuously monitor their dogs' activities, which are important to understand and guarantee their wellbeing. In this work, we introduce a camera-based monitoring system to help owners automatically monitor their dogs' activities. The system receives sequences of RGB images and uses YOLOv7 to detect the dog presence, and then applies post-processing to perform dog-centered image cropping on each input sequence. The optical flow is extracted from each sequence, and both sequences of RGB and flow are input to a two-stream EfficientNet to extract their respective features. Finally, the features are concatenated, and a bi-directional LSTM is utilized to retrieve temporal features and recognize the activity. The experiments prove that our system achieves a good performance with the F-1 score exceeding 0.90 for all activities and reaching 0.963 on average.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.46 no.3
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• pp.96-104
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• 2009

In this paper, we propose a no-reference objective Quality assessment metrics of image. The blockiness and blurring of edge areas which are sensitive to the human visual system are modeled as step functions. Blocking and blur metrics are obtained by estimating local visibility of blockiness and edge width, For the blocking metric, horizontal and vertical blocking lines are first determined by accumulating weighted differences of adjacent pixels and then the local visibility of blockiness at the intersection of blocking lines is obtained from the total difference of amplitudes of the 2-D step function which is modelled as a blocking region. The blurred input image is first re-blurred by a Gaussian blur kernel and an edge mask image is generated. In edge blocks, the local edge width is calculated from four directional projections (horizontal, vertical and two diagonal directions) using local extrema positions. In addition, the kurtosis and SSIM are used to compute the blur metric. The final no-reference objective metric is computed after those values are combined using an appropriate function. Experimental results show that the proposed objective metrics are highly correlated to the subjective data.

• Investigative Magnetic Resonance Imaging
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• v.3 no.2
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• pp.179-187
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• 1999

Purpose : This paper introduces a computationally inexpensive context-dependent classification of multi-echo MRI with Bayes compound decision model. In order to produce accurate region segmentation especially in homogeneous area and along boundaries of the regions, we propose a classification method that uses contextual information of local enighborhood system in the image. Material and Methods : The performance of the context free classifier over a statistically heterogeneous image can be improved if the local stationary regions in the image are disassociated from each other through the mechanism of the interaction parameters defined at he local neighborhood level. In order to improve the classification accuracy, we use the contextual information which resolves ambiguities in the class assignment of a pattern based on the labels of the neighboring patterns in classifying the image. Since the data immediately surrounding a given pixel is intimately associated with this given pixel., then if the true nature of the surrounding pixel is known this can be used to extract the true nature of the given pixel. The proposed context-dependent compound decision model uses the compound Bayes decision rule with the contextual information. As for the contextual information in the model, the directional transition probabilities estimated from the local neighborhood system are used for the interaction parameters. Results : The context-dependent classification paradigm with compound Bayesian model for multi-echo MR images is developed. Compared to context free classification which does not consider contextual information, context-dependent classifier show improved classification results especially in homogeneous and along boundaries of regions since contextual information is used during the classification. Conclusion : We introduce a new paradigm to classify multi-echo MRI using clustering analysis and Bayesian compound decision model to improve the classification results.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.43 no.11 s.353
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• pp.26-36
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• 2006

In this paper, we propose a cost-effective color filter may (CFA) demosaicing method for digital still cameras in which a single CCD or CMOS image sensor is used. Since a CFA is adopted, we must interpolate missing color values in the red, green and blue channels at each pixel location. While most state-of-the-art algorithms invest a great deal of computational effort in the enhancement of the reconstructed image to overcome the color artifacts, we focus on eliminating the color artifacts with low computational complexity. Using spatial correlation of the adjacent pixels, the edge-directional information of the neighbor pixels is used for determining the edge direction of the current pixel. We apply our method to the state-of-the-art algorithms which use edge-directed methods to interpolate the missing color channels. The experiment results show that the proposed method enhances the demosaiced image qualify from $0.09{\sim}0.47dB$ in PSNR depending on the basis algorithm by removing most of the color artifacts. The proposed method was implemented and verified successfully using verilog HDL and FPGA. It was synthesized to gate-level circuits using 0.25um CMOS standard cell library. The total logic gate count is 12K, and five line memories are used.