• 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.

• Journal of the Korean Society of Food Science and Nutrition
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• v.36 no.12
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• pp.1583-1588
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• 2007

PC-camera based automatic titration was executed in the acidity analyses of vinegar, milk and Takju. The average hue value (Havg) of 144 pixels in the image of the sample solution being titrated was computed and followed up at regular time intervals during titration in order to detect the titration end point. The Havg increase of 5 degrees from the first Havg was regarded as reaching at the end point in the cases of vinegar and milk. The Havg increase set up to detect the end point was 70 degrees in the case of Takju. In the case of vinegar, the volume of added titrant (0.1 N NaOH) was $21.409{\pm}0.066mL$ in manual titration and $21.403{\pm}0.055mL$ in automatic titration (p=0.841). In the case of milk, it was $1.390{\pm}0.025mL$ in manual titration and $1.388{\pm}0.027mL$ in automatic titration (p=0.907). In the case of Takju, it was $4.738{\pm}0.028mL$ in manual titration and $4.752{\pm}0.037mL$ in automatic titration (p=0.518). The high p values suggested that there were good agreements between manual and automatic titration data in all three food samples. The automatic method proposed in this article was considered to be applicable not only to acidity titrations but also to most titrations in which the end points can be detected by color change.

• Journal of the Korea Society of Computer and Information
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• v.15 no.11
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• pp.41-45
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• 2010

Image processing techniques are fundamental in human vision-based image information processing. There have been widely studied areas such as image transformation, image enhancement, image restoration, and image compression. One of research subgoals in those areas is enhancing image information for the correct information retrieval. As a fundamental task for the image recognition and interpretation, image enhancement includes noise filtering techniques. Conventional filtering algorithms may have high noise removal rate but usually have difficulty in conserving boundary information. As a result, they often use additional image processing algorithms in compensation for the tradeoff of more CPU time and higher possibility of information loss. In this paper, we propose a Fuzzy Mask Filtering algorithm that has high noise removal rate but lesser problems in above-mentioned side-effects. Our algorithm firstly decides a threshold based on fuzzy logic with information from masks. Then it decides the output pixel value by that threshold. In a designed experiment that has random impulse noise and salt pepper noise, the proposed algorithm was more effective in noise removal without information loss.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.42 no.6 s.336
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• pp.31-38
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• 2005

In this paper, we proposed an optical security system based on a gray-image exclusive-OR encryption using multi-phase separation and phase-wrapping method. For encryption, a gray image is sliced into binary images, which have the same pixel value, and these images are encrypted by modified XOR rules with binary random images. The XORed images and the binary images respectively combined and converted into full phase images, called an encrypted image and a key image. For decryption, when the encrypted image and key image are used as inputs on optical elements, Practically due to limited controllability of phase range in optical elements, the original gray image cannot be efficiently reconstructed by these optical elements. Therefore, by decreasing the phase ranges of the encrypted image and key image using a phase-wrapping method and separating these images into low-level phase images using multi-phase separation, the gray image can be reconstructed by optical elements which have limited control range. The decrytion process is simply implemented by interfering a multiplication result of encrypted image and key image with reference light. The validity of proposed scheme is verified and the effects, which are caused by phase limitation in decryption process, is analyzed by using computer simulations.