• Journal of the Institute of Electronics Engineers of Korea SP
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• v.47 no.6
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• pp.127-136
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• 2010

In multi-view video, illumination disharmony between neighboring views can occur on account of different location of each camera and imperfect camera calibration, and so on. Such discrepancy can be the cause of the performance decrease of multi-view video coding by mismatch of inter-view prediction which refer to the pictures obtained from the neighboring views at the same time. In this paper, we propose an efficient histogram-based prefiltering algorithm to compensate mismatches between the luminance and chrominance components in multi-view video for improving its coding efficiency. To compensate illumination variation efficiently, all camera frames of a multi-view sequence are adjusted to a predefined reference through the histogram matching. A Cosited filter that is used for chroma subsampling in many video encoding schemes is applied to each color component prior to histogram matching to improve its performance. The histogram matching is carried out in the RGB color space after color space converting from YCbCr color space. The effective color conversion skill that has respect to direction of edge and range of pixel value in an image is employed in the process. Experimental results show that the compression ratio for the proposed algorithm is improved comparing with other methods.

• Journal of IKEEE
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• v.13 no.4
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• pp.116-124
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• 2009

Recently the CPU performance of modem chipsets or multimedia processors of mobile phone is as high as notebook PC. That is why mobile phone has been emerged as a leading ICON on the convergence of consumer electronics. The various applications of mobile phone such as DMB, digital camera, video telephony and internet full browsing are servicing to consumers. To meet all the demands the image quality has been increasingly important. Mobile phone is a portable device which is widely using in both the indoor and outside environments, so it is needed to be overcome to deteriorate image quality depending on environmental light source. Furthermore touch window is popular on the mobile display panel and it makes contrast loss because of low transmittance of ITO film. This paper presents the image enhancement algorithm to be embedded on image enhancement SoC. In contrast enhancement, we propose Clipped histogram stretching method to make it adaptive with the input images, while S-shape curve and gain/offset method for the static application And CIELCh color space is used to sunlight readability enhancement by controlling the lightness and chroma components which is depended on the sensing value of light sensor. Finally the performance of proposed algorithm is evaluated by using histogram, RGB pixel distribution, entropy and dynamic range of resultant images. We expect that the proposed algorithm is suitable for image enhancement of embedded SoC system which is applicable for the small-sized mobile display.

• Progress in Medical Physics
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• v.20 no.4
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• pp.199-207
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• 2009

It is important to initialize Image Plate (IP) completely for removing residual latent image by sodium lamp for reliability and repeatability of computed radiography (CR) system. The purpose of this study was to evaluate latent images of computed radiography (CR) images respect to delay time after erasure of foregone latent image and its effect, and erasure level. Erasure thoroughness for CR acceptance test from American Association of Physicist in Medicine (AAPM) Report 93 (2006) was also evaluated. Measurements were made on a CR (Agfa CR 25; Agfa, BELGIUM) system. Chest postero-anterior (PA), Hand PA, L-spine lateral radiographs were chosen for evaluation. Chest phantom (3D-torso; CIRS, USA) was used for Chest PA and L-spine lateral radiography. For Hand PA radiography, projections was done without phantom. Except Hand PA radiographs, noise was increased with delay time, and ghost image was appeared on overexposed area. Effect of delay after erasure on latent image was not seen on naked eye, but standard deviation (SD) of pixel value on overexposed area was relatively higher than that of other areas. On Hand PA and Chest PA radiographs, noise were not occurred by adjustment of erasure level. On L-spine lateral images at lower erasure level than standard level, noise including ghost image were occurred because of high tube current. Erasure thoroughness of CR system in our department was to be proved by these evaluation. The results of this study could be used as a baseline for IP initialization and reliability of CR images.

• The KIPS Transactions:PartB
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• v.9B no.3
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• pp.351-358
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• 2002

Video compression based on DCT (Discrete Cosine Transform) has weakpoints of blocking artifacts and pixel loss when the resolution is changed. DWT (Discrete Wavelet Transform) based method can overcome such problems. In SAMCoW (Scalable Adaptive Motion Compensation Wavelet), one of wavelet based video coding algorithm, both intra frames and motion compensated error frames are encoded using EZW(Embedded Zerotree Wavelet) algorithm. However the property of wavelets transform coefficients of motion compensated error frames are different from that of still images. Signal energy is not highly concentrated in the lower bands which is true for most still image cases. Signal energy is rather evenly distributed over all frequency bands. This paper suggests a new video coding algorithm utilizing these properties. Spatial band coding which is known to be very effective for encoding images with relative1y high frequency components and not utilizing the interband coefficients correlation is applied instead of EZW to encode both intra and inter frames. In spatial band coding, the position and value of significant wavelet coefficients in each band are progressively transmitted. Unlike EZW, inter band coefficients correlations are not utilized in spatial band coding. It has been shown that spatial band coding gives better performance than EZW when applied to wavelet based video compression.

• The KIPS Transactions:PartB
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• v.13B no.4 s.107
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• pp.353-360
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• 2006

This paper presents a robust algorithm for segmenting a vehicle license plate area from a road image. We consider the features of license plates in three aspects : 1) edges due to the characters in the plate, 2) colors in the plate, and 3) geometric properties of the plate. In the preprocessing step, we compute the thresholds based on each feature to decide whether a pixel is inside a plate or not. A statistical approach is applied to the sample images to compute the thresholds. For a given road image, our algorithm binarizes it by using the thresholds. Then, we select three candidate regions to be a plate by searching the binary image with a moving window. The plate area is selected among the candidates with simple heuristics. This algorithm robustly detects the plate against the transformation or the difference of color intensity of the plate in the input image. Moreover, the preprocessing step requires only a small number of sample images for the statistical processing. The experimental results show that the algorithm has 97.8% of successful segmentation of the plate from 228 input images. Our prototype implementation shows average processing time of 0.676 seconds per image for a set of $1280{\times}960$ images, executed on a 3GHz Pentium4 PC with 512M byte memory.

• Journal of Bio-Environment Control
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• v.20 no.2
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• pp.63-71
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• 2011

Pattern recognition of a cucumber were conducted to detect directly the binary images by using thresholding method, which have the threshold level at the optimum intensity value. By restricting conditions of learning pattern, output patterns could be extracted from the same and similar input patterns by the algorithm. The algorithm of pattern recognition was developed to determine the position of the cucumber from a real image within working condition. The algorithm, designed and developed for this project, learned two, three or four learning pattern, and each learning pattern applied it to twenty sample patterns. The restored success rate of output pattern to sample pattern form two, three or four learning pattern was 65.0%, 45.0%, 12.5% respectively. The more number of learning pattern had, the more number of different out pattern detected when it was conversed. Detection of feature pattern of cucumber was processed by using auto scanning with real image of 30 by 30 pixel. The computing times required to execute the processing time of cucumber recognition took 0.5 to 1 second. Also, five real images tested, false pattern to the learning pattern is found that it has an elimination rate which is range from 96 to 98%. Some output patterns was recognized as a cucumber by the algorithm with the conditions. the rate of false recognition was range from 0.1 to 4.2%.

• Proceedings of the Korean Society of Medical Physics Conference
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• 2004.11a
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• pp.64-66
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• 2004

When examing patients with DRs it is necessary to remove bad pixels and lines and to correct non-uniform offsets and x-ray field. For non-uniformity correction a flat field x-ray image is needed, and to obtain it the center of detector is usually aligned with the focal spot of the x-ray tube, which is conserved when examing patients to preserve the flat field. In some of radiographic techniques, however, it is necessary to move the x-ray tube off the center position of detector or tilt the detector. We investigated the effect of detector tilting on the non-uniformity correction, and propose a method to reduce the effect using a new algorithm. The flat field of X-ray in the DR detector could be guaranteed with this result.

• The Korean Journal of Nuclear Medicine
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• v.27 no.2
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• pp.218-222
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• 1993

Lung/heart uptake ratio (L/H R) in $^{201}Tl$ myocardial perfusion scan is a reliable marker for long-term prognosis in patients with coronary artery disease. However, the value of L/H R in $^{99m}Tc-MIBI$ myocardial perfusion scan is controversial in determining the prognosis and severity of the coronary artery disease. The purpose of this study was to determine the clinical implications of L/H R in $^{99m}Tc-MIBI$ myocardial perfusion scan. Forty five patients who received $^{99m}Tc-MIBI$ myocardial perfusion scan were divided into control group and coronary artery disease (CAD) group by their clinical findings, EKGs, and $^{99m}Tc-MIBI$ myocardial perfusion scans. Twenty five patients in CAD group were divided into ischemic group and infarct group according to their results from $^{99m}Tc-MIBI$ myocardial perfusion scan. L/H R was calculated on the anterior planar view, 60 minutes after infusion of dipyridamole. Two regions of interest (ROI) were placed on the left lung area 8 pixel above the left ventricle and on the myocardial area which had the highest radioactivity. In the control group, there were no significant differences of L/H R according to sex and age. No significant difference of L/H R was found between the control and CAD group ($0.26{\pm}0.06,\;0.29{\pm}0.05$, p>0.05). In the CAD group, there was also no significant difference of L/H R between the ischemic group and infarct group ($0.29{\pm}0.07,\;0.30{\pm}0.04$, p>0.05). L/H R in CAD group did not show correlations with the defect area of stress polar map (r=0.18, p >0.05) and with the sum of severity weighted extent score or reversibility score which represent severity and extent of myocardial perfusion defect area in stress (r=0.18, p>0.05). We conclude that it is difficult to use L/H R as a marker for severity of CAD in dipyridamole $^{99m}Tc-MIBI$ myocardial perfusion scan.

• Korean Journal of Remote Sensing
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• v.27 no.5
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• pp.601-611
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• 2011

Land cover changes are occurring for a variety of reasons such as urbanization, infrastructure construction, desertification, drought, flood, and so on. Many researchers have studied the cause and effect of land cover changes, and also the methods for change detection. However, most of the detection methods are based on the dichotomy of "change" and "not change" according a threshold value. In this paper, we present a change detection method with the integration of probability, spatial autocorrelation, and hotspot detection. We used the AMOEBA (A Multidirectional Ecotope-Based Algorithm) and developed the AMOEBA-CH (core hotspot) because the original algorithm tends to produce too many clusters. Our method considers the probability of land cover changes and the spatial interactions between each pixel and its neighboring pixels using a local spatial autocorrelation measure. The core hotspots of land cover changes can be delineated by a contiguity-dominance model of our AMOEBA-CH method. We tested our algorithm in a simulation for land cover changes using NDVI (Normalized Difference Vegetation Index) data in South Korea between 2000 and 2008.

• Imaging Science in Dentistry
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• v.32 no.2
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• pp.107-111
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• 2002

Purpose : To compare the accuracy of digital subtraction images acquired by two different methods different in positioning four reference points for geometrical standardization. Materials and Methods : A total of 36 digital radiographic images of 6 volunteers were taken at the areas of the incisor, premolar, and molar of both the maxilla and mandible using the Digora system. Each image was moved 4 mm vertically and horizontally. Four oral and maxillofacial radiologists performed digital subtraction radiography between the paired images before and after movement using Emago (Oral Diagnostic Systems, Amsterdam, The Netherlands) and Sunny (Biomedisys Co., Seoul, Korea). The standard deviation of the internal gray value in Region of Interest (ROI) was statistically analyzed between the two programs using the paired t-test. Results : The standard deviation of pixel gray values from the digital subtraction images using the Sunny program were lower than that of the Emago program (p<0.05). All observers showed significant differences between each other when the Sunny program was used (p<0.05), but one observer showed a significantly higher score than other observers when they used Emago (p<0.05). The standard deviations of premolar area from both Sunny and Emago programs were significantly higher than those of anterior and molar regions (p<0.05). Conclusion: The subtracted images using the Sunny program were more accurate and sensitive than those taken using the Emago program.