• The Transactions of the Korea Information Processing Society
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• v.5 no.9
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• pp.2294-2301
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• 1998

The aim of this paper is to extract features from each news scenes for example, symbol icon which can be distinct each broadcasting corp, icon and caption which are has feature and important information for the scene in respectively, In this paper, we propose extraction methods of caption that has important prohlem of news videos and it can be classified in three steps, First of al!, we converted that input images from video frame to YIQ color vector in first stage. And then, we divide input image into regions in clear hy using equalized color histogram of input image, In last, we extracts caption using edge histogram based on vertical and horizontal line, We also propose the method which can extract news icon in selected key frames by the difference of inter-histogram and can divide each scene by the extracted icon. In this paper, we used comparison method of edge histogram instead of complex methcxls based on color histogram or wavelet or moving objects, so we shorten computation through using simpler algorithm. and we shown good result of feature's extraction.

• Journal of the Korean Society for Nondestructive Testing
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• v.27 no.5
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• pp.432-441
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• 2007

Image processing methods for an extraction of a nuclear fuel rod image and visualization methods of the RGB color data were studied with a sectional image of spent fuel assembly. The fuel rod images could be extracted by using a histogram analysis, an edge detection and RGB rotor data. In these results, a size of the spent fuel assembly could be measured by using a histogram analysis method and a shape of the spent fuel rod could be observed by using an edge detection method. Finally, a various analyses were established for status of the spent fuel assembly by realized various 3D images for the color data in an image of a spent fuel assembly.

• Journal of Digital Contents Society
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• v.18 no.4
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• pp.777-785
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• 2017

In the modern real world, we can extract and recognize some texts to get a lot of information from the scene containing them, so the techniques for extracting and recognizing text areas from a scene are constantly evolving. They can be largely divided into texture-based method, connected component method, and mixture of both. Texture-based method finds and extracts text based on the fact that text and others have different values such as image color and brightness. Connected component method is determined by using the geometrical properties after making similar pixels adjacent to each pixel to the connection element. In this paper, we propose a method to adaptively change to improve the accuracy of text region extraction, detect and correct the slope of the image using edge and image segmentation. The method only extracts the exact area containing the text by correcting the slope of the image, so that the extracting rate is 15% more accurate than MSER and 10% more accurate than EEMSER.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.8
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• pp.1540-1546
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• 2017

Digital image processing is widely used in various fields including the military, medical, image recognition system, robot and commercial sectors. But in the process of acquiring and transmitting digital images, noise is generated by various external causes. There are various types of general noise depending on the cause and form, but AWGN and impulse noise is one of the leading methods. Removing noise during image processing is essential to the pre-treatment process such as segmentation, image recognition and characteristic extraction. As such, this paper suggests an algorithm that distinguishes the non-edge area and edge area using the Canny edge to apply different filters to different areas in order to effectively remove noise from the image. To verify the effectiveness of the suggested algorithm, it was compared against existing methods using zoom images, edge images and PSNR(peak signal to noise ratio).

• The Journal of Korean Institute of Communications and Information Sciences
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• v.27 no.8A
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• pp.822-828
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• 2002

Optical flow estimation based on multi constraint approaches is frequently used for recognition of moving objects. However, the use have been confined because of OF estimation time as well as error problem. This paper shows a new method form effectively extracting movement information using the multi-constraint base approaches with sobel edge detection. The moving objects anr extraced in the input image sequence using edge detection and segmentation. Edge detection and difference of the two input image sequence gives us the moving objects in the images. The process of thresholding removes the moving objects detected due to noise. After thresholding the real moving objects, we applied the Combinatorial Hough Transform (CHT) and voting accumulation to find the optimal constraint lines for optical flow estimation. The moving objects found in the two consecutive images by using edge detection and segmentation greatly reduces the time for comutation of CHT. The voting based CHT avoids the errors associated with least squares methods. Calculation of a large number of points along the constraint line is also avoided by using the transformed slope-intercept parameter domain. The simulation results show that the proposed method is very effective for extracting optical flow vectors and hence recognizing moving objects in the images.

• Journal of Korea Society of Industrial Information Systems
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• v.23 no.6
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• pp.21-27
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• 2018

Wearing degree and uneven wearing detection algorithm using horizontal edge information is proposed in this paper. The noise in the input image is removed by bilateral filter, and then edges are extracted from the filtered image by using the proposed mask. As the tire is worn, grooves of tire shoulder or sipes are changed more than the vertical grooves. Therefore the edges from grooves of tire shoulder or sipes have more information about the tire wearing than the edges from vertical grooves. Proposed mask that is reflected this feature is used to extract the horizontal edges. After edge extraction, the edge image is represented in two-level system. The edge pixels of the binarization image are used to decide the wearing degree and uneven wearing. This proposed method can be used easily without any other equipments. The proposed method is conducted with a real vehicle, and the experimental results show the good performance of the proposed method in detecting wearing degree and uneven wearing.

• Imaging Science in Dentistry
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• v.41 no.1
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• pp.17-21
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• 2011

Purpose : The purpose of this study was to examine the patient- and treatment-related etiologic factors of external root resorption. Materials and Methods : This study consisted of 163 patients who had completed orthodontic treatments and taken the pre- and post-treatment panoramic and lateral cephalometric radiographs. The length of tooth was measured from the tooth apex to the incisal edge or cusp tip on the panoramic radiograph. Overbite and overjet were measured from the pre- and post-treatment lateral cephalometric radiographs. The root resorption of each tooth and the factors of malocclusion were analyzed with an analysis of variance. A paired t test was performed to compare the mean amount of root resorption between male and female, between extraction and non-extraction cases, and between surgery and non-surgery groups. Correlation coefficients were measured to assess the relationship between the amount of root resorption and the age in which the orthodontic treatment started, the degree of changes in overbite and overjet, and the duration of treatment. Results : Maxillary central incisor was the most resorbed tooth, followed by the maxillary lateral incisor, the mandibular central incisor, and the mandibular lateral incisor. The history of tooth extraction was significantly associated with the root resorption. The duration of orthodontic treatment was positively correlated with the amount of root resorption. Conclusion : These findings show that orthodontic treatment should be carefully performed in patients who need the treatment for a long period and with a pre-treatment extraction of teeth.

• Journal of Bio-Environment Control
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• v.1 no.1
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• pp.37-51
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• 1992

Quantizing and extracting visual features of mushroom(Lentinus edodes L.) are crucial to the sorting and grading automation, the growth state measurement, and the dried performance indexing. A computer image processing system was utilized for the extraction and measurement of visual features of front and back sides of the mushroom. The image processing system is composed of the IBM PC compatible 386DK, ITEX PCVISION Plus frame grabber, B/W CCD camera, VGA color graphic monitor, and image output RGB monitor. In this paper, an automatic thresholding algorithm was developed to yield the segmented binary image representing skin states of the front and back sides. An eight directional Freeman's chain coding was modified to solve the edge disconnectivity by gradually expanding the mask size of 3$\times$3 to 9$\times$9. A real scaled geometric quantity of the object was directly extracted from the 8-directional chain element. The external shape of the mushroom was analyzed and converted to the quantitative feature patterns. Efficient algorithms for the extraction of the selected feature patterns and the recognition of the front and back side were developed. The developed algorithms were coded in a menu driven way using MS_C language Ver.6.0, PC VISION PLUS library fuctions, and VGA graphic functions.

• The KIPS Transactions:PartB
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• v.10B no.6
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• pp.705-710
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• 2003

Recent years, as a rapid development of multimedia technology, video database system to retrieve video data efficiently seems to core technology in the oriented society. This thesis describes an efficient automatic frame detection and location method for content based retrieval of video. Frame extraction part is consist of incoming / outgoing car frame extraction and car number frame extraction stage. We gain star/end time of car video also car number frames. Frames are selected at fixed time interval from video and key frames are selected by color scale histogram and edge operation method. Car frame recognized can be searched by content based retrieval method.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.28 no.10
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• pp.676-681
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• 2015

Recently many studies being carried out to increase the light efficiency of LED. The external quantum efficiency of LED, generally the light efficiency, is determined by the internal quantum efficiency and the light extraction efficiency. The internal quantum efficiency of LED was already reached to more than 90%, but the light extraction efficiency is still insufficient compared with the internal quantum efficiency because the total internal reflection is generated in the interface between the LED chip and air. Thus, we studied about flip chip LED with PSS and performed the optical simulation which find more optimized PSS for flip chip LED to increase the light extraction efficiency. Decreasing of the total internal reflection and effect of diffused reflection according to PSS improved the light extraction efficiency. To get more higher the efficiency, we simulated flip chip with PSS that the parameters are arrangement, edge spacing, radius, height and shape of PSS.