• Korean Journal of Remote Sensing
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• v.31 no.4
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• pp.337-346
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• 2015

Water body extraction based on backscatter information is an essential process to analyze floodaffected areas from Synthetic Aperture Radar (SAR) image. Water body in SAR image tends to have low backscatter values due to homogeneous surface of water, while non-water body has higher backscatter values than water body. Non-water body, however, may also have low backscatter values in high resolution SAR image such as Kompsat-5 image, depending on surface characteristic of the ground. The objective of this paper is to present a method to increase backscatter contrast between water body and non-water body and also to remove efficiently misclassified pixels beyond true water body area. We create an entropy image using a Gray Level Co-occurrence Matrix (GLCM) and classify the entropy image into water body and non-water body pixels by thresholding of the entropy image. In order to reduce the effect of threshold value, we also propose Water Body Texture Index (WBTI), which measures simultaneously the occurrence of repeated water body pixel pair and the uniformity of water body in the binary entropy image. The proposed method produced high overall accuracy of 99.00% and Kappa coefficient of 90.38% in water body extraction using Kompsat-5 image. The accuracy analysis indicates that the proposed WBTI method is less affected by the choice of threshold value and successfully maintains high overall accuracy and Kappa coefficient in wide threshold range.

• Journal of Sensor Science and Technology
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• v.8 no.2
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• pp.154-162
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• 1999

In this paper, we acquired EBT section images of lung parenchyma using fabricated spirometric gating device and proposed new energy function based on dynamic contour model in order to extracted the contour of the lung parenchyma in EBT images. In EBT images, gray level of the lungs is lower than other region. we extracted the lungs contour using the new energy function considering gray level and contour vector of the lung parenchyma region from EBT images. As we compared the proposed method with the conventional method, we confirmed that detection method using proposed energy function was valid.

• Journal of Biomedical Engineering Research
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• v.18 no.4
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• pp.357-364
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• 1997

The early detection of breast cancer is clearly a key ingredient for reducing breast cancer mortality. Microcalcification is the only visible feature of the DCIS's(ductal carcinoma in situ) which consist 15 ~ 20% of screening-detected breast cancer. Therefore, the analysis of the shapes and distributions of microcalcifications is very significant for the early detection. The automatic detection procedures have b(:on the concern of digital image processing for many years. We proposed here one efficient method which is essentially statistical pattern classification accelerated by one representative feature, correlation coefficient. We compared the results by this additional feature with results by a simple gray level thresholding. The average detection rate was increased from 48% by gray level feature only to 83% by the proposed method The performances were evaluated with TP rates and FP counts, and also with Bayes errors.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.5 no.2
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• pp.343-348
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• 2001

In this paper we propose a noise reduction algorithm which based on cellular automata with the local median rule. It is supposed that there is no information about the features of the image that must be improved. The proposed method behavior is to locally increase or decrease the gray level differences of the image without loss of the main characteristics of the image. The dynamical behavior of these automata is completely determined by Lyapunov operators for sequential and parallel update. We have found that the automata present very fast convergence to fixed points, stability in front of random noisy images. Based on the experimental results we discuss the advantage and efficiency.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2005.05a
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• pp.115-124
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• 2005

This paper analyzes the problems that occurred in the magnification process for a fine input image and investigates a method to improve the problems. This paper applies a curve interpolation algorithm in CAD/CAM for the same test images with the existing image algorithm in order to improve the problems. As a result. the nearest neighbor interpolation. which is the most frequently applied algorithm for the existing image interpolation algorithm. shows that the identification of a magnified image is not possible. Therefore. this study examines an interpolation of gray-level data by applying a low-pass spatial filter and verifies that a bilinear interpolation presents a lack of property that accentuates the boundary of the image where the image is largely changed. The periodic B-spline interpolation algorithm used for curve interpolation in CAD/CAM can remove the blurring but shows a problem of obscuration, and the Ferguson's curve interpolation algorithm shows a more sharpened image than that of the periodic B-spline algorithm. For the future study, hereafter. this study will develop an interpolation algorithm that has an excel lent improvement for the boundary of the image and continuous and flexible property by using the NURBS. Ferguson's complex surface. and Bezier surface used in CAD/CAM engineering based on. the results of this study.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.19 no.4
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• pp.562-569
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• 2010

This paper analyzes the problems that occurred in the magnification process for a fine input image and investigates a method to improve the blurring of magnified image. This paper applies a curve interpolation algorithm in CAD/CAM for the same test images with the existing image algorithm in order to improve the blurring of magnified image. As a result, the nearest neighbor interpolation, which is the most frequently applied algorithm for the existing image interpolation algorithm, shows that the identification of a magnified image is not possible. Therefore, this study examines an interpolation of gray-level data by applying a low-pass spatial filter and verifies that a bilinear interpolation presents a lack of property that accentuates the boundary of the image where the image is largely changed. The periodic B-spline interpolation algorithm used for curve interpolation in CAD/CAM can remove the blurring but shows a problem of obscuration, and the Ferguson' curve interpolation algorithm shows a more sharpened image than that of the periodic B-spline algorithm. For the future study, hereafter, this study will develop an interpolation algorithm that has an excellent improvement for the boundary of the image and continuous and flexible property by using the NURBS, Ferguson' complex surface, and Bezier surface used in CAD/CAM engineering based on the results of this study.

• Journal of the Korea Society of Computer and Information
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• v.21 no.11
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• pp.17-21
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• 2016

Heterogeneity assessment of tumor in oncology is important for diagnosis of cancer and therapy. The aim of this study was performed assess heterogeneity tumor region in PET image using texture analysis. For assessment of heterogeneity tumor in PET image, we inserted sphere phantom in torso phantom. Cu-64 labeled radioisotope was administrated by 156.84 MBq in torso phantom. PET/CT image was acquired by PET/CT scanner (Discovery 710, GE Healthcare, Milwaukee, WI). The texture analysis of PET images was calculated using occurrence probability of gray level co-occurrence matrix. Energy and entropy is one of results of texture analysis. We performed the texture analysis in tumor, liver, and background. Assessment textural features of region-of-interest (ROI) in torso phantom used in-house software. We calculated the textural features of torso phantom in PET image using texture analysis. Calculated entropy in tumor, liver, and background were 5.322, 7.639, and 7.818. The further study will perform assessment of heterogeneity using clinical tumor PET image.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.30B no.7
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• pp.92-101
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• 1993

This paper describes algorithms to extract license plates in vehicle images. Conventional methods perform preprocessing on the entire vehicle image to produce the edge image and binarize it. Hough transform is applied to the binary image to find horizontal and vertical lines, and the license plate area is extracted using the charateristics of license plates (the boundary information of license plates). Problems with this approach are that real-time processing is not feasible due to long processing time and that the license plate area is not extracted when lighting is irregular such as at night or when the plate boundary does not show up in the image. This research uses the gray level transition characteristics of license plates to verify the digit area by examining the digit width and the gray level difference between the background area the digit area, and then extracts the plate area by testing the distance between the verified digits. This research solves the probelm of failure in extracting the license plates due to degraded plate boundary as in the conventional methods and resolves the provlem of the time requirement by processing in real time such that practical application is possible.

• Journal of the korean academy of Pediatric Dentistry
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• v.25 no.1
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• pp.171-184
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• 1998

The purpose of the study was to observe the association between the main colors of school children's drawings of dental treatment situation and their dental anxiety. The subjects of study were 688 school children from 2nd to 4th grade. Caries experience was investigated by oral examination. Questionnaire survey was done regarding children's attitude toward the dentist and dental treatment and their experience of pain and fear during the dental treatment. Colors with high frequency of use were green, blue, yellow, orange, pink, purple, gray, brown, yellow ochre, red, white, and black in order. Boys used green and blue, and girls used yellow and orange, more than each other. As the grade increased, white, yellow, and blue increased and brown decreased. Colors with high dental anxiety level were black, brown, red, white, blue, orange, yellow and green, yellow ochre, gray, pink, and purple in order, and the upper four represented 10.5% of the subjects. Children with high decayed teeth rate had a tendency to use colors of high dental anxiety level. Black color had the most obvious association with the pain and fear of dental treatment.

• The Transactions of the Korea Information Processing Society
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• v.6 no.9
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• pp.2558-2562
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• 1999

This paper proposes on the methods of noise removal and edge extraction which is done by eliminating the ambiguities of the image using normalization and minimizing the entropy. Pre-existing methods have their own peculiarities and limitations, such as gray level distributions change very slowly or two regions which having similar gray level distribution are touched. This affects on the post processing such as feature extraction, as a result, this leads to false-recognition or no-recognition. Therefore, this paper proposes on the methods which overcome these problems. Finally, the effectiveness of this paper is demonstrated by several experiments.