• Journal of the Korea Society of Computer and Information
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• v.11 no.4 s.42
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• pp.9-15
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• 2006

In this paper we propose Wilcoxon test, Median test and Van der Waerden test such as linear rank tests in two-sample location problem for detecting edges effectively in noisy images. These methods are based on detecting image intensity changes between two pixel neighborhoods using an edge-height model to perform effectively on noisy images. The neighborhood size used here is small and its shape is varied adaptively according to edge orientations. We compare and analysis the performance of these statistical edge detectors on both natural images and synthetic images with and without noise.

• Communications for Statistical Applications and Methods
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• v.6 no.3
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• pp.893-900
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• 1999

We use statistical tests which are useful for two-sample problem for detecting edges in gray-level images. An edge is detected by examining changes in gray-level value between adjacent pixel neighborhoods. Some experimental results show that nonparametric detectors such as Mann-Whitney test median test and Kolmogorov-Smirnov test perform effectively in both noisy and noise-free images while parametric T test is sensitive to noise.

• Journal of IKEEE
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• v.24 no.3
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• pp.719-726
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• 2020

A threshold-voltage sensing circuit is proposed to compensate for pixel aging in active matrix organic light-emitting diodes. The proposed threshold-voltage sensing circuit consists of sample-hold (S/H) circuits and a single-ended successive approximation register (SAR) analog-to-digital converter (ADC) with a resolution of 10 bits. To remove a scale down converter of each S/H circuit and a voltage gain amplifier with a signl-to-differentail converter, the middle reference voltage calibration and input range calibration for the single-ended SAR ADC are performed in the capacitor digital-to-analog converter and reference driver. The proposed threshold-voltage sensing circuit is designed by using a 180-nm CMOS process with a supply voltage of 1.8 V. The ENOB and power consimption of the single-ended SAR ADC are 9.425 bit and 2.83 mW, respectively.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.39 no.11
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• pp.7-13
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• 2002

BSCT 320${\times}$240 IRFPA detector module is implemented, which is a key component in uncooled thermal imaging systems. The detector module consists of two parts, infrared sensitive pixel array and read-out integrated circuit(ROIC). The BSCT 320${\times}$240 pixels are made by laser scribe process and 10-${\mu}m$ micro-bump to satisfy 50-${\mu}m$ pitch and 95-% fill-factor. The ROIC has been designed to electrically address the pixels sequentailly and to improve signal-to-noise ratio with single transistor amplifier, HPF, tunable LPF and clamp circuit. The fabricated hybrid chip of detector and ROIC has been mounted on the TEC built-in ceramic package for more stable operation and tested for lots of electrical and optical properties. The IRFA sample has shown successful properties and met with good results of fill-factor, detectivity and responsivity.

• Journal of the Korea Computer Graphics Society
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• v.2 no.1
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• pp.1-6
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• 1996

In ray tracing of 3D volume data, the color of each pixel in the image is typically obtained by accumulating the contributions of sample points on the ray cast from the pixel point. This accumulation is most naturally represented by integration. In most methods, however, it is done by numerical summation because analytical solution to the integration are hard to find. This paper shows that a semi-analytical solution can be obtained for a typical ray tracing of volume data. Tentative conclusions about the significance and usefulness of our approach are presented based on our experiments.

• The Bulletin of The Korean Astronomical Society
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• v.45 no.1
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• pp.40.4-40.4
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• 2020

Kyung Hee university invented the Transformable Reflective Telescope (TRT) for optical experiment and education. The TRT kit can transform into three optical configurations from Newtonian to Cassegrain to Gregorian by exchanging the secondary mirror. We designed the Ebert-Fastie spectrograph as an extension of the TRT kit. The primary mirror of the TRT kit serves as both collimator and camera lens, and the reflective grating as the dispersing element is placed along the optical axis of the primary mirror. We designed and fabricated the grating holder and the source units using 3D printer. Baffle was also fabricated to suppress the stray light, which was reduced by 83%. The spectrograph can observe the optical wavelength range (4000Å~7000Å). Measured resolving power (R=λ/Δλ) was ~700 with slit width of 0.18mm. The spectrograph is optimized for f/24, and the spectral pixel scale is 0.49Å/pixel with Canon 550D detector. We present the sample spectra of discharged Ne, Ar and Kr gases. The flexible setting and high performance make this spectrograph a useful tool for education and experiment.

• Current Optics and Photonics
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• v.5 no.3
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• pp.270-277
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• 2021

The adaptive sparse representation (ASR) can effectively combine the structure information of a sample dictionary and the sparsity of coding coefficients. This algorithm can effectively consider the correlation between training samples and convert between sparse representation-based classifier (SRC) and collaborative representation classification (CRC) under different training samples. Unlike SRC and CRC which use fixed norm constraints, ASR can adaptively adjust the constraints based on the correlation between different training samples, seeking a balance between l₁ and l₂ norm, greatly strengthening the robustness and adaptability of the classification algorithm. The correlation coefficients (CC) can better identify the pixels with strong correlation. Therefore, this article proposes a hyperspectral image classification method called correlation coefficients and adaptive sparse representation (CCASR), based on ASR and CC. This method is divided into three steps. In the first step, we determine the pixel to be measured and calculate the CC value between the pixel to be tested and various training samples. Then we represent the pixel using ASR and calculate the reconstruction error corresponding to each category. Finally, the target pixels are classified according to the reconstruction error and the CC value. In this article, a new hyperspectral image classification method is proposed by fusing CC and ASR. The method in this paper is verified through two sets of experimental data. In the hyperspectral image (Indian Pines), the overall accuracy of CCASR has reached 0.9596. In the hyperspectral images taken by HIS-300, the classification results show that the classification accuracy of the proposed method achieves 0.9354, which is better than other commonly used methods.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.10a
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• pp.271-274
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• 2014

This paper proposes high-performance SAO(Sample Adaptive Offset) in HEVC(High Efficiency Video Coding) encoder for Ultra HD video processing in real time. SAO is a newly adopted technique belonging to the in-loop filter in HEVC. The proposed SAO encoder hardware architecture uses three-layered buffers to minimize memory access time and to simplify pixel processing and also uses only adder, subtractor, shift register and feed-back comparator to reduce area. Furthermore, the proposed architecture consists of pipelined pixel classification and applying SAO parameters, and also classifies four consecutive pixels into EO and BO concurrently. These result in the reduction of processing time and computation. The proposed SAO encoder architecture is designed by Verilog HDL, and implemented by 180k logic gates in TSMC $0.18{\mu}m$ process. At 110MHz, the proposed SAO encoder can support 4K Ultra HD video encoding at 30fps in real time.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.5
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• pp.457-461
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• 2013

This paper proposes an image feature-based real-time RGB-D (Red-Green-Blue Depth) 3D SLAM (Simultaneous Localization and Mapping) system. RGB-D data from Kinect style sensors contain a 2D image and per-pixel depth information. 6-DOF (Degree-of-Freedom) visual odometry is obtained through the 3D-RANSAC (RANdom SAmple Consensus) algorithm with 2D image features and depth data. For speed up extraction of features, parallel computation is performed with GPU acceleration. After a feature manager detects a loop closure, a graph-based SLAM algorithm optimizes trajectory of the sensor and builds a 3D point cloud based map.

• Journal of Power System Engineering
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• v.15 no.4
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• pp.25-30
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• 2011

This study is made to provide with a method for correcting the geometric distortion of the digital radiography image by analytical approach based upon the inverse square law and Beer's law. This study is aimed to find out and improve a mathematic model of nonlinear type. Variations in the alignment of the X-ray source, the object, and imaging plate affect digital radiography images. A model which is expressed in parameter values; e.g, angle, position, absorption coefficient, length, width and pixel account of radiography source, is developed so as to match the sample image. For the best correction of the digital image that is the most similar to the model image, a correction technique based upon tangent is developed; then applied to the digital radiography images of steel tubes. As a result, the image correction is confirmed to be made successfully.