• Food Science of Animal Resources
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• v.38 no.5
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• pp.1109-1119
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• 2018

In this paper, we report the development of a nondestructive prediction model for lean meat percentage (LMP) in Korean pig carcasses and in the major cuts using a machine vision technique. A popular vision system in the meat industry, the VCS2000 was installed in a modern Korean slaughterhouse, and the images of half carcasses were captured using three cameras from 175 selected pork carcasses (86 castrated males and 89 females). The imaged carcasses were divided into calibration (n=135) and validation (n=39) sets and a multilinear regression (MLR) analysis was utilized to develop the prediction equation from the calibration set. The efficiency of the prediction equation was then evaluated by an independent validation set. We found that the prediction equation - developed to estimate LMP in whole carcasses based on six variables - was characterized by a coefficient of determination ($R^2_v$) value of 0.77 (root-mean square error [RMSEV] of 2.12%). In addition, the predicted LMP values for the major cuts: ham, belly, and shoulder exhibited $R^2_v$ values${\geq}0.8$ (0.73 for loin parts) with low RMSEV values. However, lower accuracy ($R^2_v=0.67$) was achieved for tenderloin cuts. These results indicate that the LMP in Korean pig carcasses and major cuts can be predicted successfully using the VCS2000-based prediction equation developed here. The ultimate advantages of this technique are compatibility and speed, as the VCS2000 imaging system can be installed in any slaughterhouse with minor modifications to facilitate the on-line and real-time prediction of LMP in pig carcasses.

• Journal of Korean Ophthalmic Optics Society
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• v.12 no.3
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• pp.125-130
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• 2007

The aim of this work was to study the relationship between subjective symptoms and binocular function during near work in forty one(12-17yr) schoolchildren. CISS symptom survey, amplitude of accommodation, accommodative facility, neagative relative accommodation(NRA)/positive relative accommodation(PRA) near point of convergence(NPC), heterophoria, AC/A ratios were measured. The results of measurement were compared with normal expected value of each test and classified into normal and abnormal group. Accommodative insufficiency was more general than convergence insufficiency and esophoria was greater than exophoria. NRA/PRA showed very high and AC/A ratios were very low compare with normal expected value. The results of CISS was as follows; most frequent symptom was tired, mean score was $16.63{\pm}7.49$, mean number of symptoms were $10.07{\pm}3.04$, and mean number of serious symptoms were $1.98{\pm}2.13$. After classified into 4 groups according to score of symptoms, number of symptoms, and degree of symptoms and then analyze the correlation compare with binocular vision test results. NRA was most correlated with group comparison, accommodative facility was most correlated with score of symptoms, NRA was most correlated with number of symptoms, and near horizontal phorias were most correlated with serious symptoms. NRA showed most correlative relation with near symptoms.

• Journal of Korean Ophthalmic Optics Society
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• v.15 no.3
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• pp.275-280
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• 2010

Propose: Due to the rapid growth of medical technologies and the increasing population of older people, we investigated clinical status of ocular dimensions and visual acuity for pre and post cataract surgeries of people over age 90. Methods: From March 2007 to February 2009, we investigated eighty-two eyes of forty-eight patients who had undergone cataract surgeries at an ophthalmic clinic (Ansung, Kyungi-do), investigated maximum corrected vision, axial length, anterior chamber depth and accompanied ocular diseases before and after the surgeries based on the collected data. Results: As patients aged, axial length unchanged but anterior chamber depth decreased over all due to the increase of intraocular lens thickness, and men tended to have a higher degree than women. Seventy-one (86.6%) of eighty-two eyes showed improved corrected vision than before surgeries and forty-three (52.4%) eyes could see more than visual acuity of 0.5. Conclusions: Patients with the systemic disease and accompanied ocular disease showed low vision less than 0.5 after cataract surgery compared to same healthy age peoples. But the others improved correction visual acuity more than 0.5, so the cataract surgery was surely necessary for people over 90 years old and also the presence of ocular disease could have a great influence on correction visual acuity.

• Journal of Korean Ophthalmic Optics Society
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• v.18 no.3
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• pp.329-339
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• 2013

Purpose: In this study, nutrient intake during the adolescent period is a critical time for the development of the vision. Therefore we analyzed the relationship between the obesity index and the refractive power. Methods: We used the Korean National Health and Nutrition Examination Survey 2010 document. The obesity index is classified as Broca index (less than 80.0% is low weight, 80 to 89.9% is underweight, 90.0 to 109.9% is normal, overweight is from 110.0 to 119.9%, 120.0% or more is obesity) and body mass index (BMI)(less than 18.5 is underweight, 18.6~22.9 is normal, 23.0 to 24.9 is overweight, and obesity is higher than 25.0). We analyzed correlation with the body mass index and refractive error in adolescent. Results: As shown in the statistics, according to Broca index and body mass index (BMI), the refractive power and the obesity index showed a statistically significant correlation in the ages 15 to 18. Under weight subjects are ingested 43.84% dietary fiber, vitamin C 56.55%, 35.20% iron, 31.84% of, and 38.03% potassium less than the average food intake by the standard group. Conclusions: Moderate weight with a broad variety of taking nutrition and good eating habits seems to have an effect to the good growth and the good vision.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.05a
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• pp.279-282
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• 2017

Kinect depth sensor, a depth camera developed by Microsoft as a natural user interface for game appeared as a very useful tool in computer vision field. In this paper, due to kinect's depth sensor and its high frame rate, we developed a distance measurement system using Kinect camera to test it for unmanned vehicles which need vision systems to perceive the surrounding environment like human do in order to detect objects in their path. Therefore, kinect depth sensor is used to detect objects in its field of view and enhance the distance measurement system from objects to the vision sensor. Detected object is identified in accuracy way to determine if it is a real object or a pixel nose to reduce the processing time by ignoring pixels which are not a part of a real object. Using depth segmentation techniques along with Open CV library for image processing, we can identify present objects within Kinect camera's field of view and measure the distance from them to the sensor. Tests show promising results that this system can be used as well for autonomous vehicles equipped with low-cost range sensor, Kinect camera, for further processing depending on the application type when they reach a certain distance far from detected objects.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.10 no.2
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• pp.133-140
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• 2017

In this paper, we has proposed an automatic vehicle monitoring system based on computer vision technology. The real-time display system has displayed a system that can be performed in automatic monitoring and control while meeting the essential requirements of ITS. Another advantage has that for a powerful vehicle tracking, the main obstacle handing system, which has the shadow tracking of moving objects. In order to obtain all kinds of information from the tracked vehicle image, the vehicle must be clearly displayed on the surveillance screen. Over time, it's necessary to precisely control the vehicle, and a three-dimensional model-based approach has been also necessary. In general, each type of vehicle has represented by the skeleton of the object or wire frame model, and the trajectory of the vehicle can be measured with high precision in a 3D-based manner even if the system has not running in real time. In this paper, we has applied on segmentation method to vehicle, background, and shadow. The validity of the low level vehicle control tracker was also detected through speed tracking of the speeding car. In conclusion, we intended to improve the improved tracking method in the tracking control system and to develop the highway monitoring and control system.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.1243-1244
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• 2022

In recent years, the growing interest in off-site construction has led to factories scaling up their manufacturing and production processes in the construction sector. Consequently, continuous large-scale site monitoring in low-variability environments, such as prefabricated components production plants (precast concrete production), has gained increasing importance. Although many studies on computer vision-based site monitoring have been conducted, challenges for deploying this technology for large-scale field applications still remain. One of the issues is collecting and transmitting vast amounts of video data. Continuous site monitoring systems are based on real-time video data collection and analysis, which requires excessive computational resources and network traffic. In addition, it is difficult to integrate various object information with different sizes and scales into a single scene. Various sizes and types of objects (e.g., workers, heavy equipment, and materials) exist in a plant production environment, and these objects should be detected simultaneously for effective site monitoring. However, with the existing object detection algorithms, it is difficult to simultaneously detect objects with significant differences in size because collecting and training massive amounts of object image data with various scales is necessary. This study thus developed a large-scale site monitoring system using edge computing and a small-object detection system to solve these problems. Edge computing is a distributed information technology architecture wherein the image or video data is processed near the originating source, not on a centralized server or cloud. By inferring information from the AI computing module equipped with CCTVs and communicating only the processed information with the server, it is possible to reduce excessive network traffic. Small-object detection is an innovative method to detect different-sized objects by cropping the raw image and setting the appropriate number of rows and columns for image splitting based on the target object size. This enables the detection of small objects from cropped and magnified images. The detected small objects can then be expressed in the original image. In the inference process, this study used the YOLO-v5 algorithm, known for its fast processing speed and widely used for real-time object detection. This method could effectively detect large and even small objects that were difficult to detect with the existing object detection algorithms. When the large-scale site monitoring system was tested, it performed well in detecting small objects, such as workers in a large-scale view of construction sites, which were inaccurately detected by the existing algorithms. Our next goal is to incorporate various safety monitoring and risk analysis algorithms into this system, such as collision risk estimation, based on the time-to-collision concept, enabling the optimization of safety routes by accumulating workers' paths and inferring the risky areas based on workers' trajectory patterns. Through such developments, this continuous large-scale site monitoring system can guide a construction plant's safety management system more effectively.

• Journal of the Korea institute for structural maintenance and inspection
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• v.28 no.3
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• pp.1-9
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• 2024

This study proposes a multi-scale template matching technique with image pyramids (TMI) to measure structural dynamic displacement using a vision sensor under atmospheric turbulence conditions and evaluates its displacement measurement performance. To evaluate displacement measurement performance according to distance, the three-story shear structure was designed, and an FHD camera was prepared to measure structural response. The initial measurement distance was set at 10m, and increased with an increment of 10m up to 40m. The atmospheric disturbance was generated using a heating plate under indoor illuminance condition, and the image was distorted by the optical turbulence. Through preliminary experiments, the feasibility of displacement measurement of the feature point-based displacement measurement method and the proposed method during atmospheric disturbances were compared and verified, and the verification results showed a low measurement error rate of the proposed method. As a result of evaluating displacement measurement performance in an atmospheric disturbance environment, there was no significant difference in displacement measurement performance for TMI using an artificial target depending on the presence or absence of atmospheric disturbance. However, when natural targets were used, RMSE increased significantly at shooting distances of 20 m or more, showing the operating limitations of the proposed technique. This indicates that the resolution of the natural target decreases as the shooting distance increases, and image distortion due to atmospheric disturbance causes errors in template image estimation, resulting in a high displacement measurement error.

• Journal of Korean Ophthalmic Optics Society
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• v.18 no.4
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• pp.373-383
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• 2013

Purpose: In this study, we analyzed refractive power of school children in low income family. Methods: We have done a comparative analysis with 112 subjects of low-income of 17 elementary schools in the Yeongcheon area and low-income children less than -6 D of refractive errors from the Korean National Health and Nutrition Examination Survey Report 2010. Results: Spherical equivalent (SE) with low-income group of nation was -1.99 D for right eye and -1.81 D for left eye, while high income group of nation showed -1.26 D and -1.21 D for right eye and left eye respectively. The SE with low income group in Yeongcheon area was -1.85 D for right eye and -1.81 D for left eye. The SE with orphan was -2.75 D and -2.42 D. Single parent family was -2.10 D and -1.96 D, and two parent family was -1.75 D and -1.73. Conclusions: The lack of attention to children eye care may be one of cause for myopia, so the role of the parents and teacher is very important. However, limited role of parents to children due to low income, it is necessary to provide an institutional strategy and social interest to prevent children vision' in low income family.

• Journal of Korean Ophthalmic Optics Society
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• v.17 no.3
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• pp.265-272
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• 2012

Purpose: To compare the results on myopia correction with reverse geometry lenses, effects of wearing reverse geometry lenses were evaluated for the children with low-level and high-level myopia. Methods: The research investigated the corrective effects of having worn reverse geometry lenses for one week, one month, three months and six months on a total of thirty-six persons (sixty-two eyes) between the ages of seven and fifteen, divided into three groups by the degree of their myopia; nineteen eyes(Group One) with myopia of -2.00 D and under, twenty-eight eyes(Group Two) with myopia between -2.25 D and -4 D, and fifteen eyes(Group Three) with myopia of -4.25 D and above; as shown by changes in uncorrected vision and the degree of refraction in the corneal topography, and tested for statistical similarity among the pursued results. Results: After wearing reverse geometry lenses, Group One showed an improvement in vision of 0.5, from 0.45 to 0.95, after one week, and improvements to 0.91 after one month and 1.02 after three months but, after six months, the group's vision regressed to 0.95. Group Two showed an improvement in vision of 0.43, from 0.34 to 0.77, after one week of wearing and to 0.91 after one month, to 0.97 after three months and this was statistically maintained through the remainder of six months. Group Three showed an improvement in vision of 0.55, from 0.15 to 0.7, after wearing for one week, to 0.87 after one month and to 0.91 after three months but saw a regression to 0.86 after six months. The average Sim K (simulated keratometry reading) value for Group One started from $42.84{\pm}1.17D$ and decreased to $41.48{\pm}0.98D$ after one week of wearing and continued declining through three months before increasing during the remainder of six months. Group Two began from $42.91{\pm}1.57D$ and recorded $41.78{\pm}1.58 D$ after one week, continuing the decline through three months before increasing during the remainder of six months. Group Three began at $42.64{\pm}1.64D$ and showed its Sim K value decrease to $40.77{\pm}1.20D$ after one week of wearing, increase after one month and decrease after three months and continue the decline through the remainder of six months. Conclusions: From the results of this study, wearing reverse geometry lenses had myopia-correcting effects after one week of wearing. Although there were variations in the time for such effect to take place but myopia-correcting effects were evident in all test groups.