• Physical Therapy Korea
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• v.18 no.4
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• pp.60-67
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• 2011

Ultrasonography (US) is a recent technique that has proven to be useful for assessing muscle thickness and guiding the rehabilitation decision-making of clinicians and researchers. The purpose of this study was to determine the inter-rater reliability of the US measurement of transversus abdominis (TrA), internal oblique (IO), and external oblique (EO) thicknesses for different probe locations and measurement techniques. Twenty healthy volunteers were recruited in this study. Muscle thicknesses of the transversus TrA, IO, and EO were measured three times in the hook-lying position. The three different probe locations were as follows: 1) Probe location 1 (PL1) was below the rib cage in direct vertical alignment with the anterior superior iliac spine (ASIS). 2) Probe location 2 (PL2) was halfway between the ASIS and the ribcage along the mid-axillary line. 3) Probe location 3 (PL3) was halfway between the iliac crest and the inferior angle of the rib cage, with adjustment to ensure the medial edge of the TrA. The two different techniques of thickness measurement from the captured images were as follows: 1) Muscle thickness was measured in the middle of the muscle belly, which was centered within the captured image (technique A; TA). 2) Muscle thickness was measured along a horizontal reference line located 2 cm apart from the medial edge of the TrA in the captured image (technique B; TB). The intraclass correlation coefficient (ICC [3,k]) was used to calculate the inter-rater reliability of the thickness measurement of TrA, IO and EO using the values from both the first and second examiner. In all three muscles, moderate to excellent reliability was found for all conditions (probe locations and measurement techniques) (ICC=.70~.97). In the PL1-TA condition, inter-rater reliability in the three muscle thicknesses was good to excellent (ICC=.85~.96). The reliability of all measurement conditions was excellent in IO (ICC=.95~.97). Therefore, the findings of this study suggest that TA can be applied to PL1 by clinicians and researchers in order to measure the thickness of abdominal muscles.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.2C
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• pp.141-149
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• 2007

Associating the shoulder line with head location of the human body is useful in verifying, localizing and tracking persons in an image. Since the head line and the shoulder line, what we call ${\Omega}$-shape, move together in a consistent way within a limited range of deformation, we can build a statistical shape model using Active Shape Model (ASM). However, when the conventional ASM is applied to ${\Omega}$-shape fitting, it is very sensitive to background edges and clutter because it relies only on the local edge or gradient. Even though appearance is a good alternative feature for matching the target object to image, it is difficult to learn the appearance of the ${\Omega}$-shape because of the significant difference between people's skin, hair and clothes, and because appearance does not remain the same throughout the entire video. Therefore, instead of teaming appearance or updating appearance as it changes, we model the discriminative appearance where each pixel is classified into head, torso and background classes, and update the classifier to obtain the appropriate discriminative appearance in the current frame. Accordingly, we make use of two features in fitting ${\Omega}$-shape, edge gradient which is used for localization, and discriminative appearance which contributes to stability of the tracker. The simulation results show that the proposed method is very robust to pose change, occlusion, and illumination change in tracking the head and shoulder line of people. Another advantage is that the proposed method operates in real time.

• KIPS Transactions on Software and Data Engineering
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• v.10 no.4
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• pp.125-132
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• 2021

As the layers of artificial neural network deepens, and the dimension of data used as an input increases, there is a problem of high arithmetic operation requiring a lot of arithmetic operation at a high speed in the learning and recognition of the neural network (NN). Thus, this study proposes a data dimensionality reduction method to reduce the dimension of the input data in the NN. The proposed Line-segment Feature Analysis (LFA) algorithm applies a gradient-based edge detection algorithm using median filters to analyze the line-segment features of the objects existing in an image. Concerning the extracted edge image, the eigenvalues corresponding to eight kinds of line-segment are calculated, using 3×3 or 5×5-sized detection filters consisting of the coefficient values, including [0, 1, 2, 4, 8, 16, 32, 64, and 128]. Two one-dimensional 256-sized data are produced, accumulating the same response values from the eigenvalue calculated with each detection filter, and the two data elements are added up. Two LFA256 data are merged to produce 512-sized LAF512 data. For the performance evaluation of the proposed LFA algorithm to reduce the data dimension for the recognition of handwritten numbers, as a result of a comparative experiment, using the PCA technique and AlexNet model, LFA256 and LFA512 showed a recognition performance respectively of 98.7% and 99%.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.6
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• pp.114-123
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• 2023

With the development of computer vision technology, video sensors such as CCTV are detecting incident. However, most of the current incident have been detected based on existing fixed imaging equipment. Accordingly, there has been a limit to the detection of incident in shaded areas where the image range of fixed equipment is not reached. With the recent development of edge-computing technology, real-time analysis of mobile image information has become possible. The purpose of this study is to evaluate the possibility of detecting expressway emergencies by introducing computer vision technology to dash cam. To this end, annotation data was constructed based on 4,388 dash cam still frame data collected by the Korea Expressway Corporation and analyzed using the YOLO algorithm. As a result of the analysis, the prediction accuracy of all objects was over 70%, and the precision of traffic accidents was about 85%. In addition, in the case of mAP(mean Average Precision), it was 0.769, and when looking at AP(Average Precision) for each object, traffic accidents were the highest at 0.904, and debris were the lowest at 0.629.

• Journal of the Korean Institute of Traditional Landscape Architecture
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• v.32 no.2
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• pp.55-67
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• 2014

The historic cultural landscape of East lake in Kyung river area during Joseon dynasty was very outstanding that it had many attractions of scenic beauty, however, the Han river of today is being recognized as a natural landscape and as a place with low cultural and historical traits. This study applied landscape characteristics of the cultural space of Joseon Dynasty on visual image elements of Lynch to research the landscape characteristics. The research results are as follows. When East lake was applied to visual image elements, it was recognized as a 'superb' 'paths,' and the 'edge' which signifies the boundary showed its 'superb' clarity of the East lake. For the 'node,' a turning point of direction, Dumopo represented the 'superb' awareness. As East lake, Apgujung, and Jecheonjung represented the 'superb' awareness when 'landmark' among visual image elements of Lynch was applied to the cultural space, the awareness level and reputation were proportional to the visual image elements. When pattern, structure, and meaning of the cultural space were clear and had definite identity, the 'landmark' and 'district' elements were 'superb.' It was also identified that when awareness level of space was higher, the awareness of historic cultural landscape was high as well. Therefore, considering visual awareness level of the historic cultural landscape of Han river during restoration to investigate and to conduct case studies is considered to increase the awareness level of historicity and cultural character as well as restoration of the place.

• Proceedings of the Korean Society of Medical Physics Conference
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• 2002.09a
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• pp.415-417
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• 2002

Images of microcalcification specks showed large variation in conventional radiographs of phantoms which are approved for mammography image quality standard by the American College of Radiology (ACR). This kind of variation is not appropriate for image quality standards because the number of specks are visually counted in images and that number is important in image quality evaluation. Our study using synchrotron radiation (SR) imaging revealed the overlapping of micro-sized air bubble(s) to some specks, and also the structural deformation or crackings. Eight phantoms approved by ACR from two different makers and an air-bubble phantom were examined. SR imaging was performed at a synchrotron radiation facility, SPring-8, in Japan. The image-detector was a fluorescent-screen optical-lens coupling system using a CCD camera with a spatial resolution of 6 $\square$m. Objects when imaged with longer sample-to-detector distance show edge enhancement due to a difference in refraction indices, that is refraction enhancement. Refraction-enhanced SR images revealed that some of specks carried foreign objects, which were proven to be air. In phantoms provided by one maker, attaching/overlapping airs were observed for 62 out of 150 specks (41%) , with a higher incidence for the smallest specks. A speck becomes hardly visible in a conventional radiograph when air(s) overlaps the majority part of a speck, though depending on the size of the air-inclusion and on its configuration. Those airs might have been adsorbed on a speck surface before being embedded and then introduced into the matrix together with specks. Our study using SR imaging has clearly shown the nature of defects in some mammography phantoms which seriously degrade the quality as an image standard.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.45 no.4
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• pp.50-58
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• 2008

In this paper, we propose a color transient improvement (CTI) algorithm based on image fusion to improve the color transient in the television(TV) receiver or in the MPEG decoder. Video image signals are composed of one luminance and two chrominance components, and the chrominance signals have been more band-limited than the luminance signals since the human eyes usually cannot perceive changes in chrominance over small areas. However, nowadays, as the advanced media like high-definition TV(HDTV) is developed, the blurring of color is perceived visually and affects the image quality. The proposed CTI method improves the transient of chrominance signals by exploiting the high-frequency information of the luminance signal. The high-frequency component extracted from the luminance signal is modified by spatially adaptive weights and added to the input chrominance signals. The spatially adaptive weight is estimated to minimize the ${\iota}_2-norm$ of the error between the original and the estimated chrominance signals in a local window. Experimental results with various test images show that the proposed algorithm produces steep and natural color edge transition and the proposed method outperforms conventional algorithms in terms of both visual and numerical criteria.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.25 no.5
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• pp.475-482
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• 2007

Most golfers believe that knowing yardages will improve their score. Certainly it helps with club selection. But, simple "Graphic" yardage guides being notorious for error and inaccuracies, which a serious golfer will pick immediately, only serve to erode the players enjoyment and ultimately, golf course satisfaction. Someone believes with low-level aerial photographic images, golfer will be impressed with the accuracy of the depiction, helping them play a more confident game. But, there are no mapping products in true 3-D available in the world that allows a golfer to determine shot distances in yards or meters. So, we suggest an lenticular technology for real 3-D display as a viable alternative to conventional image map solution. This technology is an image display method for the generation of multi-image effects like 3D visualization or animation. This methodology is cutting edge stereoscopic image which overcomes the limitation of conventional photo tech by recomposing and producing 3 dimensional images. A significant strength of this methods its versatility concerning display effects. The main use of the hardcopy 3-D lenticular displays is in the fields of science, education, planning, and representation. This paper gives a concise overview of the lenticular foil technology and describes the production of the true 3-D yardage book of golf courses. For this study, 3-D effects are achieved and evaluated with the lenticular display by incorporation multiple synthetic images based on digital topographic terrain model and by using the two images of the actual stereopair.

• Journal of Sensor Science and Technology
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• v.7 no.2
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• pp.124-130
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• 1998

High-speed 3D vision systems are essential for autonomous robot or vehicle control applications. In our study, a stereo vision process has been developed. It consists of three steps : extraction of edges in right and left images, matching corresponding edges and calculation of the 3D map. This process is implemented in a VME 150/40 Imaging Technology vision system. It is a modular system composed by a display, an acquisition, a four Mbytes image frame memory, and three computational cards. Programmable accelerator computational modules are running at 40 MHz and are based on TMS320C31 DSP with a $64{\times}32$ bit instruction cache and two $1024{\times}32$ bit internal RAMs. Each is equipped with 512 Kbytes static RAM, 4 Mbytes image memory, 1 Mbytes flash EEPROM and a serial port. Data transfers and communications between modules are provided by three 8 bit global video bus, and three local configurable pipeline 8 bit video bus. The VME bus is dedicated to system management. Tasks between DSPs are distributed as follows: two DSPs are used to edges detection, one for the right image and the other for the left one. The last processor computes the matching process and the 3D calculation. With $512{\times}512$ pixels images, this sensor generates dense 3D maps at a rate of about 1 Hz depending of the scene complexity. Results can surely be improved by using a special suited multiprocessors cards.

• Journal of the Institute of Convergence Signal Processing
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• v.8 no.1
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• pp.22-31
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• 2007

The proposed algorithm in this paper is based on the wavelet decomposition and the energy computation of composed blocks so the amount of calculation and complexity is minimized by adaptively replacing the DWT coefficients and managing the resources effectively. We are now living in the world of a lot. of multimedia applications for many digital electric appliances and mobile devices. Among so many multimedia applications, the digital image compression is very important technology for digital cameras to store and transmit digital images to other sites and JPEG2000 is one of the cutting edge technology to compress still images efficiently. The digital cm technology is mainly using the digital image compression features so that those images could be efficiently saved locally and transferred to other sites without any losses. JPEG2000 standard is applicable for processing the digital images usefully to keep, send and receive through wired and/or wireless networks. The discrete wavelet transform (DWT) is one of the main differences to the previous digital image compression standard such as JPEG, performing the DWT to the entire image rather than splitting into many blocks. Several digital images m tested with this method and restored to compare to the results of conventional DWT which shows that the proposed algorithm get the better result without any significant degradation in terms of MSE & PSNR and the number of zero coefficients when the energy based adaptive DWT is applied.