• Radiation Oncology Journal
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• v.27 no.4
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• pp.240-248
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• 2009

Purpose: To provide a simple research tool that may be used to analyze a dose volume histogram from different radiation therapy planning systems for NTCP (Normal Tissue Complication Probability), OED (Organ Equivalent Dose) and so on. Materials and Metohds: A high-level computing language was chosen to implement Niemierko's EUD, Lyman-Kutcher-Burman model's NTCP, and OED. The requirements for treatment planning analysis were defined and the procedure, using a developed GUI based program, was described with figures. The calculated data, including volume at a dose, dose at a volume, EUD, and NTCP were evaluated by a commercial radiation therapy planning system, Pinnacle (Philips, Madison, WI, USA) for comparison. Results: The volume at a special dose and a dose absorbed in a volume on a dose volume histogram were successfully extracted using DVH data of several radiation planning systems. EUD, NTCP and OED were successfully calculated using DVH data and some required parameters in the literature. Conclusion: A simple DVH analyzer program was developed and has proven to be a useful research tool for radiation therapy.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.3A
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• pp.181-188
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• 2009

This study presented the basic data for determining reasonable construction method and evaluating the structural safety of suspension bridges. The analytical program was developed to conduct initial shape and natural frequency analysis, construction stage analysis and reliability analysis considering construction sequences. This program was based on analysis models of suspension bridges and reliability theories used in the previous study. A construction method was established considering various construction variables such as construction order and construction direction of girder and synchronized construction of main and side span etc. The dynamic construction analysis by a construction scheme was conducted with the developed program. Benefits of the characteristic analysis by the construction scheme was presented estimating structural response of critical members respectively. Structural reliability analysis by construction stage was conducted considering aleatory uncertainties. The safety of suspension bridges by established construction method was quantitatively estimated using reliability index and failure probability. Analytical results were re-estimated considering epistemic uncertainties, and critical percentile distributions of risk at the construction stage were presented using the frequency histogram.

• The Korean Journal of Applied Statistics
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• v.28 no.6
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• pp.1147-1161
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• 2015

Nowadays we are considering and analyzing not only classical data expressed by points in the p-dimensional Euclidean space but also new types of data such as signals, functions, images, and shapes, etc. Symbolic data also can be considered as one of those new types of data. Symbolic data can have various formats such as intervals, histograms, lists, tables, distributions, models, and the like. Up to date, symbolic data studies have mainly focused on individual formats of symbolic data. In this study, it is extended into datasets with both histogram and multimodal-valued data and a divisive clustering method for the mixed feature-type symbolic data is introduced and it is applied to the analysis of industrial accident data.

• Journal of Korea Society of Industrial Information Systems
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• v.23 no.1
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• pp.87-96
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• 2018

In this paper, we propose a method to determine whether there is a defect by using the similarity between ROIs (Region of Interest) of the standard image and ROIs of the image which is corrected in position and rotation after capturing the vehicle headlight. The degree of similarity is determined by the template matching based on the histogram of image, which is a some modification of the method provided by OpenCV where template matching is performed on the raw image not the histogram. The proposed method is compared with the basic method of OpenCV for performance analysis. As a result of the analysis, it was found that the proposed method showed better performance than the OpenCV method, showing the accuracy close to 100%.

• The Journal of the Korea Contents Association
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• v.9 no.11
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• pp.225-230
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• 2009

Filtering has been used to improve the image quality not only in MRI but in most image processing fields. In this paper, modified Fermi-Direc filter was transformed in various shapes, and then the optimum shape was designed. In addition, Newly made filter was applied in real clinic, which showed the obvious improvement in image quality. In conclusion, filtered image was superior to original image in contrast and sharpness. Then, this was proved by the histogram of R, G, B channel used for the quantitative analysis.

• Journal of Korean Academy of Oral and Maxillofacial Radiology
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• v.24 no.2
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• pp.439-450
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• 1994

Recently, the digital image was introduced into radiological image. The digital image has the power of contrast enhancement, histogram control, and other digitally enhancement. At the point of the resolution, periapical radiograph is superior to the digital image, but enhanced digital procedure improves the diagnostic ability of the digital image. The purpose of this study was to evaluate the diagnostic ability of artificial proximal caries in conventional radiographs, digital radiographs and enhanced digital radiographs (histogram specification). ROC (Receiver Operating Characteristic) analysis and paired t-test were used for the evaluation of detectability, and following results were acquired: 1. The mean ROC area of conventional radiographs was 0.9274. 2. The mean ROC area of unenhanced digital image was 0.9168. 3. The mean ROC area of enhanced digital image was 0.9339. 4. The diagnostic ability of three imaging methods was not significant difference(p>0.05). So, the digital images had similar diagnostic ability of artificial proximal caries to conventional radiographs. If properly enhanced digital image, it may be superior to conventional radiographs.

• The Journal of the Korea Contents Association
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• v.5 no.2
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• pp.267-274
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• 2005

In this paper, we proposed an algorithm which cognize hand pose in real time using only image. Hand recognizes using edge orientation histogram which comes under a constant quantity of 2D appearance because hand pose is intricate. This method suit hand pose recognition in real time because it extracts hand space accurately, has little computation quantify, and is less sensitive to lighting change using color information in complicated background. Method which reduces recognition error using principal component analysis method to can recognize through hand shape presentation direction change is explained. A case that hand shape changes by turning 3D also by using this method is possible to recognize. Besides, principal component space creation time is reduced remarkably because edge directional data is used.

• Journal of Korean Academy of Oral and Maxillofacial Radiology
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• v.25 no.2
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• pp.375-387
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• 1995

The purpose of this study was to quantitatively evaluated experimental tooth root resorption for digital radiography. For this study, experimentally three root sites were used, and radiograms were taken with standardized apparatus. Digital imaging system were consisted of NEC PC-980l(computer), TRINITRON(monitor), SONY XC-711 CCD camera. The display monitor had a resolution of 512X512 pixels. The obtained results were as follows: 1. In the difference of the four X-ray film of the contrast correction, the contrast difference was one gray scale variation at mean value. 2. Viewing of the view box of the periapical radiographs, experimental tooth root resorption of the periapical area of the first premolar, middle of mesial surface of the first molar mesial root, middle of lingual surface of the first molar distal root were recognized by increased diameter. 3. On the analysis by histogram, the periapical area of the first premolar, the middle of mesial surface of the first molar mesial root were each recognized tooth root resorption of the 5,6,7 pixel, 2,4,5 pixel by increased diameter. 4. On the analysis by histogram, the middle of lingual surface of the first molar distal root was each recognized tooth root resorption of the none, 3,6 pixel by increased diameter.

• Proceedings of the IEEK Conference
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• 2000.07a
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• pp.450-453
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• 2000

In this paper, an automated segmentation algorithm is proposed for MR brain images using T1-weighted, T2-weighted, and PD images complementarily. The proposed segmentation algorithm is composed of 3 steps. In the first step, cerebrum images are extracted by putting a cerebrum mask upon the three input images. In the second step, outstanding clusters that represent inner tissues of the cerebrum are chosen among 3-dimensional (3D) clusters. 3D clusters are determined by intersecting densely distributed parts of 2D histogram in the 3D space formed with three optimal scale images. Optimal scale image best describes the shape of densely distributed parts of pixels in 2D histogram. In the final step, cerebrum images are segmented using FCM algorithm with it’s initial centroid value as the outstanding cluster’s centroid value. The proposed segmentation algorithm complements the defect of FCM algorithm, being influenced upon initial centroid, by calculating cluster’s centroid accurately And also can get better segmentation results from the proposed segmentation algorithm with multi spectral analysis than the results of single spectral analysis.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.10a
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• pp.97-100
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• 2013

In this paper, we propose a detection method of the character rather than cursive, containing many components of the vertical and horizontal direction in complex background image. The characters have many dense corners but the background has few sparse corners. So we use harris corner detector and cluster the corners by using the position of the detected corners for detecting character regions. To merge or filter character regions, we analysis a histogram of gray image of character regions. In each improved region, we compare histograms of R, G, B channels to detect characters.