• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.464-467
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• 2007

All image data acquisition systems for example the digital camera and digital camcorder, use the image sensor to convert the image data (light) into electronic data. These image sensors are used in satellite camera for high quality and resolution image data. There are two kinds of image sensors, the one is the CCD (charge coupled device) detector sensor and the other is the CMOS (complementary metal-oxide semiconductor) image sensor. The CCD sensor control system has more complex than the CMOS sensor control system. For the high quality image data on CCD sensor, the precise timing control signal and the several voltage sources are needed in the control system. In this paper, the comparison of the CCD with CMOS sensor, the CCD sensor characteristic, and the control system will be described.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.79-82
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• 2005

Recently the necessity of road data is still being increased in industrial society, so there are many repairing and new constructions of roads at many areas. According to the development of government, city and region, the update and acquisition of road data for GIS (Geographical Information System) is very necessary. In this study, the fusion method with range data(3D Ground Coordinate System Data) and Intensity data in stand alone LiDAR data is used for road extraction and then digital image processing method is applicable. Up to date Intensity data of LiDAR is being studied. This study shows the possibility method for road extraction using Intensity data. Intensity and Range data are acquired at the same time. Therefore LiDAR does not have problems of multi-sensor data fusion method. Also the advantage of intensity data is already geocoded, same scale of real world and can make ortho-photo. Lastly, analysis of quantitative and quality is showed with extracted road image which compare with I: 1,000 digital map.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1244-1248
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• 2005

In this paper, we propose fuzzy c-means (FCM) to solve recognition errors in invariant range image, multi-pose face recognition. Scale, center and pose error problems were solved using geometric transformation. Range image face data was digitized into range image data by using the laser range finder that does not depend on the ambient light source. Then, the digitized range image face data is used as a model to generate multi-pose data. Each pose data size was reduced by linear reduction into the database. The reduced range image face data was transformed to the gradient face model for facial feature image extraction and also for matching using the fuzzy membership adjusted by fuzzy c-means. The proposed method was tested using facial range images from 40 people with normal facial expressions. The output of the detection and recognition system has to be accurate to about 93 percent. Simultaneously, the system must be robust enough to overcome typical image-acquisition problems such as noise, vertical rotated face and range resolution.

• Journal of Conservation Science
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• v.37 no.3
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• pp.220-231
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• 2021

The use of digital copies of film-based analog images and the introduction of digital radiographic imaging systems using image plates gradually replace the non-destructive radiationirradiation method of Cultural Heritage. The quality of images obtained from this technique is affected by conditions such as tube voltage, tube current, and exposure time, type of image acquisition medium, distance of the artifacts from the image acquisition medium, and thickness of artifacts. In this study, we evaluated the grayscale image obtained using GE's Computed Radiograhpy (CR) imaging system, the transmission characteristics of the X-ray source for each tree type (pine, chestnut, sawtooth oak, ginkgo) used in wooden Cultural Heritage, and the signal-to-noise ratio (SNR) and contrast. The GE's CR imaging were analyzed using the Duplex wire image quality indicator, line-pair gauges.

• The Korean Journal of Nuclear Medicine Technology
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• v.18 no.2
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• pp.8-16
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• 2014

Purpose The quantitative analysis of gallbladder emptying is very important in diagnosis of motility disorder of gallbladder and in biliary physiology. The GBEF obtain the statics aquisition method or the dynamic acquisition method in two ways. The purpose of this study is to compare the GBEF value of statics acquisition method and the dynamic acquisition method. And we find the best way for calculate GBEF. Materials and Methods The quantitative hepatobiliary scan with $^{99m}Tc$-mebrofenin was performed of 27 patients. Initial images were acquired statically, for 60 min after injection of the radioactive tracer. And if the gallbladder is visualized to 60 min, performed stimulation of gallbladder (1egg, 200 mL milk). After that, started acquisition of dynamic image for 30 min. After that, image of after fatty meal of the statics method were acquired on equal terms with 60 min image. The statics GBEF was calculated using the images of before fatty meal and post fatty meal by the statics method. The dynamic GBEF was calculated using the images of time of maximum bile juice uptake ($T_{max}$) and time of minimum bile juice uptake ($T_{min}$) images from the gallbladder time-activity curve. A bile juice is secreted from gallbladder while eating a fatty meal. that is named early GBEF and that was calculated using before fatty meal image of the statics method and 1 min image of the dynamic method. Results The result saw very big difference between two according to $T_{max}$. The result, were as follows. 1) In case of less than 1 min, the dynamic mean GBEF was $40.1{\pm}21.7%$, the statics mean GBEF was $51.5{\pm}23.6%$ in 16 cases. The early mean GBEF was $14.0{\pm}29.1%$. The GBEF of statics method was higher because that include secreted bile juice while performed stimulation of gallbladder. A difference of GB counts according to acquisition method and the early bile juice counts was $17.6{\pm}14.8%$ and $13.5{\pm}15.3%$. 2) In case of exceed than 1 min, the dynamic mean GBEF was $31.0{\pm}19.7%$, the statics mean GBEF was $21.3{\pm}19.4%$ in 7 cases. The early GBEF was $-6.9{\pm}4.9%$. The GBEF of dynamic method was higher because that include concentrated bile juice to $T_{max}$. A difference of GB counts according to acquisition method and the early bile juice counts was $14.3{\pm}7.3%$ and $5.9{\pm}3.9%$. Conclusion The statics method is very easy and simple, but in case of $T_{max}$ delay, the GBEF can be lower. The dynamic method is able to calculate accurately in case of $T_{max}$ delay, but in case of $T_{max}$ is less than 1 min, the GBEF can be lower because dynamic GBEF exclude secreted bile juice while performed stimulation of gallbladder. The best way to calculate GBEF is to scan with dynamic method preferentially and to choose suitable method between the two way after conform $T_{max}$ on the T-A curve of the dynamic method.

• International Journal of Internet, Broadcasting and Communication
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• v.7 no.1
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• pp.15-19
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• 2015

The depth information of an image is used in a variety of applications including 2D/3D conversion, multi-view extraction, modeling, depth keying, etc. There are various methods to acquire depth information, such as the method to use a stereo camera, the method to use the depth camera of flight time (TOF) method, the method to use 3D modeling software, the method to use 3D scanner and the method to use a structured light just like Microsoft's Kinect. In particular, the depth camera of TOF method measures the distance using infrared light, whereas TOF sensor depends on the sensitivity of optical light of an image sensor (CCD/CMOS). Thus, it is mandatory for the existing image sensors to get an infrared light image by bundling several pixels; these requirements generate a phenomenon to reduce the resolution of an image. This thesis proposed a measure to acquire a high-resolution image through gradual area movement while acquiring a low-resolution image through pixel bundling method. From this measure, one can obtain an effect of acquiring image information in which illumination intensity (lux) and resolution were improved without increasing the performance of an image sensor since the image resolution is not improved as resolving a low-illumination intensity (lux) in accordance with the gradual pixel bundling algorithm.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.11C
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• pp.1527-1540
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• 2004

In this paper, velocity measurement of fast moving object for traffic information acquisition using line sampling of image is proposed. Velocity measurement for traffic information acquisition of moving object is that the first sample line and second sample line on the road is set, then car is detected by using difference image method between time-variance hue data of image when car is passing two sample lines and hue data of the reference image, and velocity of the car is measured by using frame number of video which is occupied by two sample lines. Identification of the car is performed by hue of the detected car between the first sample line and second sample line, respectively To examine the propriety of the proposed algorithm, identification and velocity measurement for driving car is evaluated. The evaluated results is that it is identified by hue data of car passing two sample lines, and the velocity measurement for driving car is less than 3% comparing with X-band speed gun.

• Journal of Korea Technical Association of The Pulp and Paper Industry
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• v.44 no.2
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• pp.18-28
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• 2012

This study was to develop a novel automatic system for measuring St$\ddot{o}$ckigt sizing degree and contact angle at a time. The conventional methods to measure sizing degree had serious problems in obtaining significant differences according to different dosages of a sizing agent, and moreover they disclosed unique limitation due to liquid types used and tester's subjectivity. However, the newly developed system could get reproducible results through total automation of all procedures including liquid dropping, image acquisition and measurement of both St$\ddot{o}$ckigt sizing degree and contact angle. For the St$\ddot{o}$ckigt sizing test, the automatic system could measure sizing degree with more definite differences according to different dosage of AKD, compared to the conventional method. For the contact angle test, the automatic system showed a similar trend to the conventional method but had smaller contact angles due to distortion of an image focus by a sheet curl than the conventional testing machine. The problem from the image out of focus due to specimen curl will be overcome with adopting a new specimen holder for the future system.

• Tunnel and Underground Space
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• v.12 no.1
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• pp.1-9
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• 2002

Recently, the use of image analysis methods and commercial equipments has been extensively increased in the field of rock engineering. However the problem of errors involved in the image acquisition and subsequent analysis procedure has been frequently neglected. In addition there has been few studies dealing with this problem. So proper color calibration method is needed to be developed for the objectivity and improvement of reliability on image analysis of rock. Color calibration method using standard color rendition chart was adopted on this study. Color calibration and error analysis were carried out for the image acquired from granite rock samples. As a result, comparison among other rock images and improvement of reliability on whole analysis were possible.

• Journal of information and communication convergence engineering
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• v.6 no.1
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• pp.80-85
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• 2008

Images are often corrupted by noises during signal acquisition and transmission. Among those noises, additive white Gaussian noise (AWGN) and impulse noise are most representative. For different types of noise have different characters, how to remove them separately from degraded image is one of the most fundamental problems. Thus, a modified image restoration algorithm is proposed in this paper, which can not only remove impulse noise of random values, but also remove the AWGN selectively. The noise detection step is by calculating the intensity difference and the spatial distance between pixels in a mask. To divide two different noises, the method is based on three weighted parameters. And the weighted parameters in the filtering mask depend on spatial distances, positions of impulse noise and standard deviation of AWGN. We also use the peak signal-to-noise ratio (PSNR) to evaluate restoration performance, and simulation results demonstrate that the proposed method performs better than conventional median-type filters, in preserving edge details.