• Journal of the Korea Society of Computer and Information
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• v.13 no.6
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• pp.155-162
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• 2008

The quality of the fruits is measured by a lot of parameters. The grader of the fruits to measure the size of them is using the rotation drum method. Therefore when we classify the size of the fruits, they will be damaged. Also the optical grader used for estimating the degree of the saccharinity will incur high cost for it. In the proposed system, to select the characteristics of the fruits, three cameras are used. Because the information such as the volume and the degree of the maturity is used to classify the fruits, the degree of the saccharinity can't be estimated itself, but the information such as the color and the damage of the fruits can be estimated. Therefore, because we don't need the digital image with high resolution, we can develop the grader system of the fruit with low cost. To evaluate the performance of the proposed system, we compared it with the sight estimation and then we classified the sample. The result shows the accuracy of 96.7%.

• Proceedings of the Korean Vacuum Society Conference
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• 2000.02a
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• pp.211-211
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• 2000

Carbon nanotubes (CNTs) have been spotlighted as one of promising field emission displays(FEDs). For the first time, to authors knowledge, we have developed the 9" color CNT-FEDs with the resolution of 240x576 lines. The 9" CNT-FEDs with diode-type and triode-type structures are presented. The well-dispersed CNT paste was squeezed onto the metal-patterned cathode glass. For the anode plate, the Y2O2S:Eu, ZnS:Ag,Cl low-voltage phosphors were printed for red, green, and blue colors, respectively. The vacuum-packaged panel maintained the vacuum level of 1x10-7 Torr. The uniform moving images vacuum-packaged panel maintained the vacuum level of 1x10-7 Torr. The uniform moving images were demonstrated at 2 V/um. High brightness of 800, 200, and 150cd/m2 was observed on the green, red, and blue phosphors at V/um, respectively. Field emission characteristics of a triode-type CNT-FED were simulated using a finite element method. the resultant field strength on the cathode was modulated by gate bias and emitted electrons were focused on the anode. A relatively uniform emission image was experimentally achieved at the 800V anode. A relatively uniform emission image was experimentally achieved at the 800V anode and the 50-180 V gate biases. Energy distribution of electrons emitted from CNTs was measured using an energy analyzer. The maximum peak of energy curve corresponded to the Fermi energy level of CNTs. The whole fabrication processed of CNT-FEDs were fully scalable and reproducible. Our CNT-FEDs has demonstrated the high potential of large-area and full-color applications with very low cost fabrication and low power consumption.

• Journal of the Korean Institute of Intelligent Systems
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• v.24 no.4
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• pp.372-378
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• 2014

Noise in biomedical X-ray image degrades the quality so that it might causes to decrease the accuracy of diagnosis. Especially the noise reduction techniques is quite essential for low-dose biomedical X-ray images obtained from low radiation power in order to protect patients, because their noise level is usually high to well discriminate objects. This paper proposes an efficient method to remove the noise in low-dose X-ray images while preserving the edges with diverse resolutions. In the proposed method, a noisy image is at first decomposed into several images with different resolutions in pyramidal representation, then the stable map of edge confidence is obtained from each of analyzed image using a fuzzy logic-based edge detector. This map is used to adaptively determine the parameter for guided filters, which eliminate the noise while preserving edges in the corresponding image. The filtered images in the pyramid are extended and synthesized into a resulted image using interpolation technique. The superiority of proposed method compared to the median, bilateral, and guided filters has been experimentally shown in terms of noise removal and edge preserving properties.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.37 no.1
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• pp.67-76
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• 2024

In this paper, we present a DIP-MLS testing method that combines digital image processing with a rigid body-based MLS differencing approach to measure mechanical variables and analyze the impact of target location and image resolution. This method assesses the displacement of the target attached to the sample through digital image processing and allocates this displacement to the node displacement of the MLS differencing method, which solely employs nodes to calculate mechanical variables such as stress and strain of the studied object. We propose an effective method to measure the displacement of the target's center of gravity using digital image processing. The calculation of mechanical variables through the MLS differencing method, incorporating image-based target displacement, facilitates easy computation of mechanical variables at arbitrary positions without constraints from meshes or grids. This is achieved by acquiring the accurate displacement history of the test specimen and utilizing the displacement of tracking points with low rigidity. The developed testing method was validated by comparing the measurement results of the sensor with those of the DIP-MLS testing method in a three-point bending test of a rubber beam. Additionally, numerical analysis results simulated only by the MLS differencing method were compared, confirming that the developed method accurately reproduces the actual test and shows good agreement with numerical analysis results before significant deformation. Furthermore, we analyzed the effects of boundary points by applying 46 tracking points, including corner points, to the DIP-MLS testing method. This was compared with using only the internal points of the target, determining the optimal image resolution for this testing method. Through this, we demonstrated that the developed method efficiently addresses the limitations of direct experiments or existing mesh-based simulations. It also suggests that digitalization of the experimental-simulation process is achievable to a considerable extent.

• Journal of Intelligence and Information Systems
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• v.29 no.2
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• pp.171-187
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• 2023

When a person's face is recognized through a recording device such as a low-pixel surveillance camera, it is difficult to capture the face due to low image quality. In situations where it is difficult to recognize a person's face, problems such as not being able to identify a criminal suspect or a missing person may occur. Existing studies on face recognition used refined datasets, so the performance could not be measured in various environments. Therefore, to solve the problem of poor face recognition performance in low-quality images, this paper proposes a method to generate high-quality images by performing image quality improvement on low-quality facial images considering various environments, and then improve the performance of facial feature point detection. To confirm the practical applicability of the proposed architecture, an experiment was conducted by selecting a data set in which people appear relatively small in the entire image. In addition, by choosing a facial image dataset considering the mask-wearing situation, the possibility of expanding to real problems was explored. As a result of measuring the performance of the feature point detection model by improving the image quality of the face image, it was confirmed that the face detection after improvement was enhanced by an average of 3.47 times in the case of images without a mask and 9.92 times in the case of wearing a mask. It was confirmed that the RMSE for facial feature points decreased by an average of 8.49 times when wearing a mask and by an average of 2.02 times when not wearing a mask. Therefore, it was possible to verify the applicability of the proposed method by increasing the recognition rate for facial images captured in low quality through image quality improvement.

• IEIE Transactions on Smart Processing and Computing
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• v.3 no.1
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• pp.10-18
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• 2014

From the perspective of reducing the sampling cost of color images at high resolution, block-based compressive sensing (CS) has attracted considerable attention as a promising alternative to conventional Nyquist/Shannon sampling. On the other hand, for storing/transmitting applications, CS requires a very efficient way of representing the measurement data in terms of data volume. This paper addresses this problem by developing a measurement-coding method with the proposed customized Huffman coding. In addition, by noting the difference in visual importance between the luma and chroma channels, this paper proposes measurement coding in YCbCr space rather than in conventional RGB color space for better rate allocation. Furthermore, as the proper use of the image property in pursuing smoothness improves the CS recovery, this paper proposes the integration of a low pass filter to the CS recovery of color images, which is the block-based ${\ell}_{20}$-norm minimization. The proposed coding scheme shows considerable gain compared to conventional measurement coding.

• International Journal of Advanced Culture Technology
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• v.8 no.3
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• pp.260-268
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• 2020

Currently, it is usually a 3D scanner processing method as a laser method. However, the laser method has a disadvantage of slow scanning speed and poor precision. Although optical scanners are used as a method to compensate for these shortcomings, optical scanners are closely related to the distance and precision of the object, and have the disadvantage of being expensive. In this paper, 3D scanner using variable focus lens-based structured light module with improved measurement precision was designed to be high performance, low price, and usable in industrial fields. To this end, designed a telecentric optical system based on a variable focus lens and connected to the telecentric mechanism of the step motor and lens to adjust the focus of the variable lens. Designed a connection structure with optimized scalability of hardware circuits that configures a stepper motor to form a system with a built-in processor. In addition, by applying an algorithm that can simultaneously acquire high-resolution texture image and depth information and apply image synthesis technology and GPU-based high-speed structured light processing technology, it is also stable for changes to external light. We will designed and implemented for further improving high measurement precision.

• Journal of Radiation Protection and Research
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• v.45 no.1
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• pp.35-44
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• 2020

Background: Cadmium zinc telluride (CZT) is a promising material because of a high detection efficiency, good energy resolution, and operability at room temperature. However, the cost of CZT dramatically increases as its size increases. In this study, to achieve a large effective volume with relatively low cost, an array structure comprised of individual virtual Frisch-grid CZT detectors was proposed. Materials and Methods: The prototype consisted of 2 × 2 CZTs, a holder, anode and cathode printed circuit boards (PCBs), and an application-specific integrated circuit (ASIC). CZTs were used and the non-contacting shielding electrode method was applied for virtual Frisch-grid effect. An ASIC was used, and the holder and the PCBs were fabricated. In the current system, because the CZTs formed a common cathode, a total of 5 channels were assigned for data processing. Results and Discussion: An experiment using ¹³⁷Cs at room temperature was conducted for 10 minutes. Energy and timing information was acquired and the depth of interaction was calculated by the timing difference between the signals of both electrodes. Based on obtained three-dimensional position information, the energy correction was carried out, and as a result the energy spectra showed the improvements. In addition, a Compton image was reconstructed using the iterative method. Conclusion: The virtual Frisch-grid CZT detector based on the array structure was developed and the energy spectra and the Compton image were successfully acquired.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2012.10a
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• pp.75-77
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• 2012

In this paper, We proposed that real-time pupil detection using local binarization at each region of eyes in image. In image obtained a single low-resolution web-camera, we detect a region of face using haar-like feature and then detect each region of eyes depending upon the rate of width and height of region of face respectively. In each region of eyes, we detect the pupil after local preprocessing and binarizing. This pupil detection can be variously used for HCI(Human-Computer Interface) systems.

• Journal of the Institute of Convergence Signal Processing
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• v.6 no.3
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• pp.120-126
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• 2005

This paper presents the 3D wavelet based video compression system using quad-tree algorithm. The 3D wavelet based video compression system removes the temporal correlation of the input sequences using the motion compensation filter and decomposes the spatio-temporal subband using the spatial wavelet transform. The proposed system allocates the higher bit rate to the low frequency image of the 3D wavelet sequences and improves the 0.64dB PSNR performance of the reconstructed image in comparison with that of H.263. In addition to the limitation on the propagation of the motion compensation error by the 3D wavelet transform, the proposed system progressively transmits the input sequence according to the resolution and rate scalability.