• Journal of the Korea Society of Computer and Information
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• v.29 no.10
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• pp.129-135
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• 2024

In this paper, we design and implement a worker musculoskeletal assessment platform. The three core components of this platform are the Mobile App, the Modeling Server, and the Web Platform. The Mobile App is an Android application developed in Kotlin, targeting Android platform 12 (S) and Android API Level 31 devices. The app utilizes the camera to capture various worker motion data and transmits it to the Modeling Server. The Modeling Server is implemented using Node.js. This server converts the worker's motion data-such as points, skeleton, and x, y, z coordinate data, measured by the mobile app-into multidimensional arrays. It then applies machine learning frameworks like TensorFlow and Keras to predict the worker's posture. The worker posture learning model is built using Teachable Machine. The Web Platform is developed using React and visualizes the worker's movements as 3D animations along a timeline. The machine learning-based worker musculoskeletal assessment platform developed in this paper aims to contribute to minimizing musculoskeletal disorders in workers at industrial sites.

• Progress in Medical Physics
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• v.25 no.3
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• pp.151-156
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• 2014

The purpose of this study was to confirm the feasibility of imaging of therapy region from the boron neutron capture therapy (BNCT) using the measurement of the prompt gamma ray depending on the neutron flux. Through the Monte Carlo simulation, we performed the verification of physical phenomena from the BNCT; (1) the effects of neutron according to the existence of boron uptake region (BUR), (2) the internal and external measurement of prompt gamma ray dose, (3) the energy spectrum by the prompt gamma ray. All simulation results were deducted using the Monte Carlo n-particle extended (MCNPX, Ver.2.6.0, Los Alamos National Laboratory, Los Alamos, NM, USA) simulation tool. The virtual water phantom, thermal neutron source, and BURs were simulated using the MCNPX. The energy of the thermal neutron source was defined as below 1 eV with 2,000,000 n/sec flux. The prompt gamma ray was measured with the direction of beam path in the water phantom. The detector material was defined as the lutetium-yttrium oxyorthosilicate (Lu0,6Y1,4Si0,5:Ce; LYSO) scintillator with lead shielding for the collimation. The BUR's height was 5 cm with the 28 frames (bin: 0.18 cm) for the dose calculation. The neutron flux was decreased dramatically at the shallow region of BUR. In addition, the dose of prompt gamma ray was confirmed at the 9 cm depth from water surface, which is the start point of the BUR. In the energy spectrum, the prompt gamma ray peak of the 478 keV was appeared clearly with full width at half maximum (FWHM) of the 41 keV (energy resolution: 8.5%). In conclusion, the therapy region can be monitored by the gamma camera and single photon emission computed tomography (SPECT) using the measurement of the prompt gamma ray during the BNCT.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.47 no.6
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• pp.39-47
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• 2010

A research of image-based articulated pose estimation has some problems such as detection of human feature, precise pose estimation, and real-time performance. In particular, various methods are currently presented for recovering many joints of human body. We propose the novel numerical inverse kinematics improved with the UKF(unscented Kalman filter) in order to estimate the human pose in real-time. An existing numerical inverse kinematics is required many iterations for solving the optimal estimation and has some problems such as the singularity of jacobian matrix and a local minima. To solve these problems, we combine the UKF as a tool for optimal state estimation with the numerical inverse kinematics. Combining the solution of the numerical inverse kinematics with the sampling based UKF provides the stability and rapid convergence to optimal estimate. In order to estimate the human pose, we extract the interesting human body using both background subtraction and skin color detection algorithm. We localize its 3D position with the camera geometry. Next, through we use the UKF based numerical inverse kinematics, we generate the intermediate joints that are not detect from the images. Proposed method complements the defect of numerical inverse kinematics such as a computational complexity and an accuracy of estimation.

• Journal of Korea Multimedia Society
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• v.16 no.6
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• pp.764-781
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• 2013

In this paper, we propose a highly precise vehicle detection method with low false alarm using billboard sweep stereo matching and multi-stage hypothesis generation. First, we capture stereo images from cameras established in front of the vehicle and obtain the disparity map in which the regions of ground plane or background are removed using billboard sweep stereo matching algorithm. And then, we perform the vehicle detection and tracking on the labeled disparity map. The vehicle detection and tracking consists of three steps. In the learning step, the SVM(support vector machine) classifier is obtained using the features extracted from the gabor filter. The second step is the vehicle detection which performs the sobel edge detection in the image of the left camera and extracts candidates of the vehicle using edge image and billboard sweep stereo disparity map. The final step is the vehicle tracking using template matching in the next frame. Removal process of the tracking regions improves the system performance in the candidate region of the vehicle on the succeeding frames.

• Nutrition Research and Practice
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• v.9 no.2
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• pp.207-212
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• 2015

BACKGROUND/OBJECTIVES: The Recaller app was developed to help individuals record their food intakes. This pilot study evaluated the usability of this new food picture application (app), which operates on a smartphone with an embedded camera and Internet capability. SUBJECTS/METHODS: Adults aged 19 to 28 years (23 males and 22 females) were assigned to use the Recaller app on six designated, nonconsecutive days in order to capture an image of each meal and snack before and after eating. The images were automatically time-stamped and uploaded by the app to the Recaller website. A trained nutritionist administered a 24-hour dietary recall interview 1 day after food images were taken. Participants' opinions of the Recaller app and its usability were determined by a follow-up survey. As an evaluation indicator of usability, the number of images taken was analyzed and multivariate Poisson regression used to model the factors determining the number of images sent. RESULTS: A total of 3,315 food images were uploaded throughout the study period. The median number of images taken per day was nine for males and 13 for females. The survey showed that the Recaller app was easy to use, and 50% of the participants would consider using the app daily. Predictors of a higher number of images were as follows: greater interval (hours) between the first and last food images sent, weekend, and female. CONCLUSIONS: The results of this pilot study provide valuable information for understanding the usability of the Recaller smartphone food picture app as well as other similarly designed apps. This study provides a model for assisting nutrition educators in their collection of food intake information by using tools available on smartphones. This innovative approach has the potential to improve recall of foods eaten and monitoring of dietary intake in nutritional studies.

• Journal of Biosystems Engineering
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• v.28 no.4
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• pp.343-350
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• 2003

This study was conducted to find out the coefficient relationships between intensity values of image processing and biological/physical parameters of soil in greenhouses. Soil images were obtained by an image processing system consisting of a personal computer and a CCD earners. A software written in Visual C$\^$++/ systematically integrated the functions of image capture, image processing, and image analysis. Image processing data of the soil samples were analyzed by the method of regression analysis. The results are as follows. For detecting soil density of unbroken soil samples, the highest correlation coefficients of 0.82 and 0.84, respectively were obtained fur R-value and S-value among image processing data while it was 0.97 for G-value. Considering the relationship between biological characteristics and image processing data of soil in greenhouse, the correlation was found generally low. For pH of unbroken soil sample, the correlation coefficients were found 0.87, 0.85, and 0.94, respectively with G, I, and H values of image processing data. In the case of bacteria, any correlation was not found with the image processing data For Actinomyctes, they were 0.86 and 0.85, respectively with G-value and B-value of image processing data showing high correlation coefficient compared to the other variables. The correlation coefficient between Fungi and H-value was shown 0.88, the highest among the variables higher than 0.8 while the other variables showed low correlation. For broken soil samples from greenhouse, the relation between biological parameter and image processing data were rarely shown in this study. The results of this study indicated that most of correlation coefficient between the variables were usually lower than 0.01. Accordingly, it was assumed that the soil should be used without broken to fairly estimate biological characteristics using CCD camera.

• Journal of Animal Environmental Science
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• v.7 no.3
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• pp.177-182
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• 2001

This study was conducted to find out the coefficient relationships between intensity values image processing and pollution density of slurries. Slurry images were obtained from the image processing system using personnel computer and CCD-camera. Software, written in Visual $c^{++}$, combined the functions of the image capture, image processing and image analysis. The data of image processing for slurries were analyzed by the method of regression analysis. The results are as follows. 1. Red(R)-values among image processing data were obtained the highest correlation coefficient 0.9213 for detecting COD. Also, green(G)-value were obtained the highest correlation coefficient 0.9019 fur detecting BOD. Blue(B)-value could not find significant values to detect the pollution resources density. 2. Hue(H)-values among image processing data were obtained the highest correlation coefficient 0.9466 for detecting BOD. This fact could be used in detecting BOD 3. Green(G)-value, GRAY-value, Hue(H)-value, Saturation(5)-value and Intensity(I)-value were the correlation coefficient more than 0.8 for BOD. Hue(H)-value was higher correlation coefficient than any other value. It was possible to detect pollution density of slurries by using the image processing system. 4. Red(R)-value, GRAY-value and Saturation(5)-value were obtained the correlation coefficient more than 0.8 for detecting COD. a-value had the highest correlation coefficient Among these values. It was possible to detect density indirectly by using the image processing system. 5. SS-density were obtained the correlation coefficient less than 0.8 by using the image processing system. The density of $NH_4$-N and $NO_3$-N were obtained correlation coefficient less than 0.2.

• Journal of the Korean Crystal Growth and Crystal Technology
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• v.23 no.2
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• pp.93-100
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• 2013

Many researches have been carried out to reduce and/or to capture the major global warming gases. Especially, the hydrate formation mechanisms were intensively investigated for carbon dioxide sequestration and storage process applications. In this study, the characteristics of film-type crystal growth mechanism of carbon dioxide hydrate were comprehensively examined. Carbon dioxide hydrate crystal was formed in semi-batch type stir reactor at various pressure conditions while the temperature was fixed to be constant to reduce and minimize the guest gas solubility effects. A supply gas composition was 99.999 % of Carbon dioxide, the observation data was collected by optical microscope adopted CCD camera (Nikon DS-5M/Fi1/2M-U2). This study revealed that the guest gas pressure changes significantly altered the crystal growth mechanism and film growth rate of carbon dioxide hydrate crystal. The critical pressure of the carbon dioxide hydrate of crystal growth mechanism change was found to be 2.0 MPa. The capillary force and gas concentration gradient also significantly changed the film-type crystal growth mechanism of carbon dioxide hydrate crystal.

• The KIPS Transactions:PartB
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• v.14B no.5
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• pp.329-336
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• 2007

In this paper we propose both the construction of image DB including information on the shooting location and direction of the captured outdoor images and the efficient retrieval method from the DB. Furthermore, for the automatic extraction of the location and direction information, we suggest to have the Digital Camera equipped with an expandable GPS modulo which has a function to calculate the location and direction and also to utilize GPS IFD tags in the EXIF. Then that will make it possible for us to retrieve quickly and precisely the target image with its geography and other objects on the ground included. In the previous retrieval method based only on the location, we eel some extra useless images due to the fact that all the images in the ROI(Region Of Interest) are searched on one condition, radius. However, with the proposed method in this paper, we can not only retrieve all the images selectively within the ROI but also achieve nearly 100% of precision when we search for the target images within DOI(Direction Of Interest) with another condition, direction, added. Applying this method to an image retrieval system, we can classify or retrieve natural images based on the location and direction information, which, in turn, will be vitally useful to diverse industrial fields such as disaster alarm system, fire and disaster prevention system, traffic information system, and so forth.

• Korean Journal of Remote Sensing
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• v.35 no.6_2
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• pp.1149-1160
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• 2019

In this study, two radiometric correction methods deriving reflectance from UAV multispectral image for monitoring forest vegetation were applied and evaluated. Multispectral images were obtained from a small multispectral camera having 5 spectral bands. Reflectance were derived by applying the two methods: (1) the direct method using downwelling irradiance measurement and (2) the empirical line correction method by linking a set of field reflectance measured simultaneous with the image capture. Field reflectance were obtained using a spectroradiometer during the flight and used for building the linear equation for the empirical method and for the validation of image reflectance derived. Although both methods provided the high correlations between field reflectance and image-derived reflectance, their distributions were somewhat different. While the direct method provided rather stable and consistent distribution of reflectance all over the entire image area, the empirical method showed very unstable and inconsistent reflectance distribution. The direct method would be more appropriate for relatively wide area that requires more time to acquire image and may vary in downwelling irradiance and atmospheric conditions.