• Proceedings of the KIEE Conference
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• 2000.11d
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• pp.747-749
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• 2000

In this paper, we proposed color stereo matching algorithm using dynamic programming. The conventional gray stereo matching algorithms show blur at depth discontinuities and non-existence of matching pixel in occlusion lesions. Also it accompanies matching error by lack of matching information in the untextured region. This paper defines new cost function makes up for the problems happening in conventional gray stereo matching algorithm. New cost function contain the following properties. I) Edge points are corresponded to edge points. ii) Non-edge points are corresponded to non-edge points. iii) In case of exiting the amount of edges, the cost function has some weight in proportion to path distance. Proposed algorithm was applied in various images obtained by parallel camera model. As the result, proposed algorithm showed improved performance in the aspect of matching error and processing in the occlusion region compared to conventional gray stereo matching algorithms.

• Journal of Biomedical Engineering Research
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• v.11 no.2
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• pp.217-226
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• 1990

This paper presents a new algorithm that extracted lung region in X-ray and enhanced the region. With a lung region that was extracted by histogram threshold value, it was diffi cult to detect perfect lung boundary. Therefore we presented perfect lung boundary detection method using apex detection and apex region restoration. Also, by applying modified equalization algorithm and presented function to inside of lung region, we want to give help to automatic diagnosis In X-ray chest image. Presented main line trace algorithm gave good result in detection of lung boundary And, as apex detection method using lung row and column gray level average value found more correct place of lung than the rpethod of prior algorithm, we succeeded perfect lung region detection, Also, presented function that had lung region's gray level distribution characteristic was very effective to image enhancement.

• Proceedings of the IEEK Conference
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• 2000.07a
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• pp.441-445
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• 2000

This study is to segment white matter, gray matter, and cerebrospinal fluid(CSF) on a brain MR image of coronal section and to calculate the volume of each. First, we segmented the whole region of a brain from a black colored background, a skull and a fat layer. Then, we calculated the partial volume of each component, which was present in scanning finite thickness, with the arithmetical analysis of gray value from the internal region of a brain showing the blurring effects on the basis of the MR image forming principle. Calculated partial volumes of white matter, gray matter and CSF were used to determine the threshold for the segmentation of each component on a brain MR image showing the blurring effects. Finally, the volumes of segmented white matter, gray matter, and CSF were calculated. The result of this study can be used as the objective diagnostic method to determine the degree of brain atrophy of patients who have neurodegenertive diseases such as Alzheimer’s disease and cerebral palsy.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.40 no.1
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• pp.1-9
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• 2003

In this paper, we propose a new method dispersing spatially C(Cyan), M(Magenta), Y(Yellow) instead of K(black) in the bright region. The overlapping of black dots decreases brightness in the dark region, and black dots are very sensitive to human visual system in the bright region. Therefore, to avoid this problem, bright and dark gray region in the color image is considered in the proposed approach. A new method which uses CMY simultaneously in single mask is proposed, and CMY dots are used dispersing spatially for the bright region instead of black dot by this method. And tone curve connection is used to consider the gray level of dark region. In previous method, BNM (Blue Noise Mask) has high granularity and a narrow dynamic range. But the proposed method has the low granularity, wide dynamic range, and high contrast properties. Because the proposed method uses three times dots spatially in the different position than a conventional BNM, it can express more spatial information and a similar gray level compared with BNM.

• Journal of KIISE:Software and Applications
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• v.33 no.11
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• pp.942-952
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• 2006

We propose an automatic segmentation method for identifying pulmonary structures using gray-level information of chest CT images. Our method consists of following five steps. First, to segment pulmonary structures based on the difference of gray-level value, we select the threshold using optimal thresholding. Second, we separate the thorax from the background air and then the lungs and airways from the thorax by applying the inverse operation of 2D region growing in chest CT images. To eliminate non-pulmonary structures which has similar intensities with the lungs, we use 3D connected component labeling. Third, we segment the trachea and left and right mainstem bronchi using 3D branch-based region growing in chest CT images. Fourth, we can obtain accurate lung boundaries by subtracting the result of third step from the result of second step. Finally, we select the threshold in accordance with histogram analysis and then segment radio-dense pulmonary vessels by applying gray-level thresholding to the result of the second step. To evaluate the accuracy of proposed method, we make a visual inspection of segmentation result of lungs, airways and pulmonary vessels. We compare the result of the conventional region growing with the result of proposed 3D branch-based region growing. Experimental results show that our proposed method extracts lung boundaries, airways, and pulmonary vessels automatically and accurately.

• Journal of KIISE:Software and Applications
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• v.29 no.11
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• pp.803-808
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• 2002

This paper describes automatic methods for detection of kidney and kidney tumor on abdominal CT scans. The abdominal CT images were digitalized using a film digitizer and a gray-level threshold method was used to segment the kidney. Based on texture analysis results, which were perform on sample images of kidney tumors, SEED region of kidney tumor was selected as result of homogeneity test. The average and standard deviation, which are representative statistical moments, were used to as an acceptance criteria for homogeneous test. Region growing method was used to segment the kidney tumor from the center pixel of selected SEED region using a gray-level value as an acceptance criteria for homogeneity test. These method were applied to 113 images of 9 cases, which were scanned by GE Hispeed Advantage CT scanner and digitalized by Lumisvs LS-40 film digitizer. The sensitivity was 85% and there was no false-positive results.

• Journal of agriculture & life science
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• v.50 no.2
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• pp.25-32
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• 2016

A severe outbreak of gray mold on kenaf (Hibiscus cannabinus L.) was observed on kenaf grown in the research field of Gyeongsangnam-do Agricultural Research and Extension Services, Jinju, Korea in 2014. Gray mold appeared on young plants as gray-brown velvety mold covering stems and leaves. Infections that girdled the stem caused wilting above the infected area and developed a canker. The casual fungus formed grayish brown colonies on potato dextrose agar. The conidia were one celled, mostly ellipsoid or ovoid in shape, colorless or pale brown in color, and 6-18 × 4-10 ㎛ in size. The conidiophores were 15-32 ㎛ in length. These measurements and taxonomic characteristics were most similar to those of Botrytis. DNA sequencing and phylogenetic analysis of the complete internal transcribed spacer rRNA gene region confirmed that the fungal isolates were indeed Borytis cinerea. Koch's postulates were supported by pathogenicity tests conducted on healthy plants. On the basis of mycological characteristics and pathogenicity test on host plants, the fungus was identified as Botrytis cinerea. To the best of our knowledge, this is the first report of a gray mold caused by B. cinerea on kenaf in Korea.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.8C
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• pp.1062-1068
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• 2004

In this paper, we introduce a new gray level comer detection method to recognize corner points accurately. The new corner detector divides the corner region into many homocentric circles according to the window size, and calculates the corner response and angle of corner area about each layer to get an accurate corner point. The new corner detector has a hierarchical structure so it can detect corner point more quickly than general gray level corner detector

• Journal of KIISE:Software and Applications
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• v.32 no.6
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• pp.502-511
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• 2005

In this paper, we propose a hybrid analysis method(HAM) based on gray-intensity information from natural scene images. The HAM is composed of GIA(Gray-intensity Information Analysis) and SMA(Split/Merge Analysis). Our experimental results show that the proposed approach is superior to conventional methods both in simple and complex images.

• Journal of the Korean Society of Radiology
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• v.14 no.6
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• pp.781-790
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• 2020

Tract-Based Spatial Statics (TBSS) after obtaining the image by examining a diffusion tensor image that can determine the presence or absence of damage to the cerebral white matter and gray matter for middle-aged men aged 30 to 50 with the starting age of drinking as a variable. As a result of measuring and analyzing the FA (fractional anisotropy) value of the brain gray matter region to the hippocampal region nerve fibers, the lower the alcohol start age in all regions, the lower the anisotropy measurement value, but the FA value was statistically significant. The study results indicated by the FA results measured in this study are that the earlier the drinking start age, the more severe the morphological changes in all neurological and anatomical brain regions in the hippocampal region of the brain gray matter and seriously affect the nerve fiber tissue. It can be said to harm and damage nerve fibers and affect functional morphological variations associated with alcohol.