• 한국정보디스플레이학회:학술대회논문집
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• 2005.07b
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• pp.1398-1400
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• 2005

A novel data driver for passive matrix organic lightemitting devices (PM-OLEDs) with high gray scale images was designed. The proposed circuit consisted of a main current bias circuit as well as sample & hold circuits in each channel of the data driver to compensate a current offset. These results indicate that a data driver designed by using the current offset compensation technique holds promise for poten tial applications in PM-OLED displays with high gray scale images.

• Proceedings of the KIEE Conference
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• 2004.11c
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• pp.632-634
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• 2004

First for high-qualify images and reducing process-error and driving speed, the designed 8-bit data driving circuit consists of a constant transconductance bias circuit, D-F/Fs by shift registers using static transmission gates, 1st latch and 2nd latch by tristate inverters, level shifters, current steering segmented D/A converters by 4MSB thermometer decoder and 4LSB weighted type. Second, we designed gray amp for power saving. These data driving circuits are designed with $0.35-{\mu}m$ CMOS technologies at 3.3 V and 18 V power supplies and simulated with HSPICE.

• Journal of Korea Multimedia Society
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• v.8 no.10
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• pp.1347-1359
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• 2005

We propose an efficient block classification of the document images using the second-order statistical texture features computed from spatial gray level dependence matrix (SGLDM). We studied on the techniques that will improve the block speed of the segmentation and feature extraction speed and the accuracy of the detailed classification. In order to speedup the block segmentation, we binarize the gray level image and then segmented by applying smoothing method instead of using texture features of gray level images. We extracted seven texture features from the SGLDM of the gray image blocks and we applied these normalized features to the BP (backpropagation) neural network, and classified the segmented blocks into the six detailed block categories of small font, medium font, large font, graphic, table, and photo blocks. Unlike the conventional texture classification of the gray level image in aerial terrain photos, we improve the classification speed by a single application of the texture discrimination mask, the size of which Is the same as that of each block already segmented in obtaining the SGLDM.

• Transactions of Materials Processing
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• v.27 no.6
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• pp.339-346
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• 2018

This study investigated the microstructure and wear properties of extruded hyper-eutectic Al-Si (15wt.%) alloy in an engine oil environment. The wear mechanism of the material was also analyzed and compared to conventional gray cast iron. In microstructural observation results of Al-15wt.%Si alloy, primary Si phase ($45.3{\mu}m$) and eutectic Si phase ($3.1{\mu}m$) were found in the matrix, and the precipitations of $Mg_2Si({\beta}^{\prime})$, $Al_2Cu({\theta}^{\prime})$ and $Al_6(Mn,Fe)$ were also detected. In the case of gray cast iron, ferrite and pearlite were observed. It was also observed that flake graphite ($20-130{\mu}m$) were randomly distributed. Wear rates were lower in the Al-Si alloy as compared to those of gray cast iron in all load conditions, confirming the outstanding wear resistance of Al-15wt.%Si alloy in engine oil environment. In the $4kg_f$ condition, the wear rate of gray cast iron was $6.0{\times}10^{-5}$ and that of Al-Si measured $0.8{\times}10^{-5}$. The microstructures after wear of the two materials were analyzed using scanning electron microscope (SEM) and electron backscatter diffraction (EBSD). The primary Si and eutectic Si of Al-Si alloy effectively mitigated the abrasive wear, and the Al matrix effectively endured to accept a significant amount of plastic deformation caused by wear.

• Journal of Korea Foundry Society
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• v.2 no.2
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• pp.10-17
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• 1982

This study has been carried out to determine the change of mechanical properties and microstructures by the heattreatment to relieve the residual stresses for gray cast irons. The results have been obtained from the experiment as follows; 1) The annealing above $600^{\circ}C$ for the stress relieving of gray cast iron decrease the tensile strength and hardness 2) The decrease reates of tensile strength and hardness of gray cast iron after annealing above $600^{\circ}C$ are increased with increasing the holding time. 3) The gray cast iron containing the elements of Mn, Cr has increased the heating temperature for the decrease of tensile strength and hardness. 4) The decrease of mechanical properties by annealing are assumed that the formation of ferrite takes placed from the decomposition of eutectoid cementite in the matrix.

• 한국정보디스플레이학회:학술대회논문집
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• 2004.08a
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• pp.673-675
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• 2004

This study proposes controller with voltage-compensated drivers for producing gray-scaled pictures on passive matrix organic light emitting diodes (PMOLEDs) panels. The controller includes voltage type drivers so the output impedance of the driver is far less than that of the current-type driver. Its low output impedance provides better electron-optical properties than those of traditional current drivers. A free running clock and a group of counters are applied to the gray-scaled function so that phase lock loop (PLL) circuit can be reduced in the controller. A pre-charge function is used to enhance performance of the luminance of an active OLED pixel. As a result, distribution of the low gray level portion is achieved linear relationship with input data. In this work, the digital part of the proposed controller is implemented using FPGA chips, and analog parts are combined with a digital-analog converter (DAC) and analog switches. A still image is displayed on a $48^{\ast}64$ PMOLEDs panel to assess the luminance performance fir the controller. Based on its cost requirement and luminance performance, the controller is qualified to join the market for driving PMOLEDs panels.

• Journal of Biomedical Engineering Research
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• v.5 no.2
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• pp.121-126
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• 1984

A new approach to texture classification for quantitative ultrasound liver diagnosis using run difference matrix was developed. The run difference matrix comprised the gray level difference along with a distances. From this run difference matrix, we defined several vectors and parameters such as DOD, DGD, DAD vector, SHP, SMO, SMG, LDE, LDEL etc.Each parameter values calculated in fatty, cirrhotic, normal and chronic hepatitic liver images were plotted in a plane and we found that RDM method was more sensitive to small structural changes than the conventional run length method and showed improved classification ability between the diseases.

• Journal of Information Processing Systems
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• v.13 no.3
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• pp.590-598
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• 2017

Recently, there has been an increase in the number of hazardous events, such as fire accidents. Monitoring systems that rely on human resources depend on people; hence, the performance of the system can be degraded when human operators are fatigued or tensed. It is easy to use fire alarm boxes; however, these are frequently activated by external factors such as temperature and humidity. We propose an approach to fire detection using an image processing technique. In this paper, we propose a fire detection method using multichannel information and gray level co-occurrence matrix (GLCM) image features. Multi-channels consist of RGB, YCbCr, and HSV color spaces. The flame color and smoke texture information are used to detect the flames and smoke, respectively. The experimental results show that the proposed method performs better than the previous method in terms of accuracy of fire detection.

• Journal of information and communication convergence engineering
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• v.20 no.1
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• pp.58-64
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• 2022

Breast ultrasonic reading is critical as a primary screening test for the early diagnosis of breast cancer. However, breast ultrasound examinations show significant differences in diagnosis based on the difference in image quality according to the ultrasonic equipment, experience, and proficiency of the examiner. Accordingly, studies are being actively conducted to analyze the texture characteristics of normal breast tissue, positive tumors, and malignant tumors using breast ultrasonography and to use them for computer-assisted diagnosis. In this study, breast ultrasonography was conducted to select 247 ultrasound images of 71 normal breast tissues, 87 fibroadenomas among benign tumors, and 89 malignant tumors. The selected images were calculated using a statistical method with 21 feature parameters extracted using the gray level co-occurrence matrix algorithm, and classified as normal breast tissue, benign tumor, and malignancy. In addition, we proposed five feature parameters that are available for computer-aided diagnosis of breast cancer classification. The average classification rate for normal breast tissue, benign tumors, and malignant tumors, using this feature parameter, was 82.8%.

• Proceedings of the Korea Information Processing Society Conference
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• 2011.04a
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• pp.410-413
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• 2011

본 논문에서는 도로 영상에서 검출된 자동차 영상을 종류별 분류를 위해 효과적인 질감 특징정보 기반의 자동차 종류별 분류 방안을 제안한다. 제안한 연구에서는 운전자의 안전운전지원을 위해 도로상에서 검출된 자동차 영역과 자신의 차량과 거리를 추정하기 위해 검출된 자동차의 종류를 인식할 필요가 있다. 즉, 인식된 자동차의 종류에 따라 차량 간 거리를 추정에 필요한 파라미터로 사용할 수 있기 때문이다. 따라서 본 연구에서는 검출된 자동차 영상들로부터 GLCM(gray-level co-occurrence matrix)의 7가지의 특징정보들을 추출하고 SVM을 사용하여 학습 한 후 자동차의 종류(승용, 화물, 버스)를 분류하는 방법을 제안한다. GLCM은 영상이 가진 질감 정보를 효율적으로 분석함으로써 영역의 밝기 변화 정도, 거침 정도, 픽셀 분포 정도 등을 표현하기 때문에 영상내의 포함된 영역을 분류하는데 효과적이다. 제안한 방법을 실제 자동차 규모별 분류에 적용한 결과 약 83%의 분류 성공률을 제시하였다.