• Journal of the Korea Organic Resources Recycling Association
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• v.31 no.1
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• pp.85-100
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• 2023

In this study, in order to improve the installation periodical inspection method of waste treatment facilities, we conducted on-site surveys of waste treatment facilities classified into six fields, grasped the problems of inspection methods, and made improvements accordingly. And revised the inspection method for waste treatment facilities. As a result, in the field of incineration and incineration heat recovery, inspection methods such as total temperature measurement and one-year TMS data comparison using a thermal imaging camera were established. And for the safety of the inspected person, it was applied so that the waste can be replaced with a document without opening it. In the case of landfill facilities, the details regarding the use of video information processing equipment and the management of facilities covering the upper part of the landfill facility are presented in the law, but the items that do not have a inspection methods were applied to the inspection method. In the case of Food Waste Treatment Facility, inspection methods were put in place to ensure compliance with standards for foul-smelling fish in odor control, a major cause of complaints. As a result, 10 out of 18 improvement proposals were reflected in the incineration and sterilization grinding, cement kiln, and incineration heat recovery facilities, and 11 out of 12 improvement proposals were reflected in the landfill facility. In the case of food distribution waste treatment facilities, 10 out of 12 improvement proposals were reflected, and a total of 31 inspection methods were improved.

• Journal of Intelligence and Information Systems
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• v.29 no.2
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• pp.171-187
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• 2023

When a person's face is recognized through a recording device such as a low-pixel surveillance camera, it is difficult to capture the face due to low image quality. In situations where it is difficult to recognize a person's face, problems such as not being able to identify a criminal suspect or a missing person may occur. Existing studies on face recognition used refined datasets, so the performance could not be measured in various environments. Therefore, to solve the problem of poor face recognition performance in low-quality images, this paper proposes a method to generate high-quality images by performing image quality improvement on low-quality facial images considering various environments, and then improve the performance of facial feature point detection. To confirm the practical applicability of the proposed architecture, an experiment was conducted by selecting a data set in which people appear relatively small in the entire image. In addition, by choosing a facial image dataset considering the mask-wearing situation, the possibility of expanding to real problems was explored. As a result of measuring the performance of the feature point detection model by improving the image quality of the face image, it was confirmed that the face detection after improvement was enhanced by an average of 3.47 times in the case of images without a mask and 9.92 times in the case of wearing a mask. It was confirmed that the RMSE for facial feature points decreased by an average of 8.49 times when wearing a mask and by an average of 2.02 times when not wearing a mask. Therefore, it was possible to verify the applicability of the proposed method by increasing the recognition rate for facial images captured in low quality through image quality improvement.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.3A
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• pp.297-307
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• 2010

Recently, maintenance engineering and technology for civil and building structures have begun to draw big attention and actually the number of structures that need to be evaluate on structural safety due to deterioration and performance degradation of structures are rapidly increasing. When stiffness is decreased because of deterioration of structures and member cracks, dynamic characteristics of structures would be changed. And it is important that the damaged areas and extent of the damage are correctly evaluated by analyzing dynamic characteristics from the actual behavior of a structure. In general, typical measurement instruments used for structure monitoring are dynamic instruments. Existing dynamic instruments are not easy to obtain reliable data when the cable connecting measurement sensors and device is long, and have uneconomical for 1 to 1 connection process between each sensor and instrument. Therefore, a method without attaching sensors to measure vibration at a long range is required. The representative applicable non-contact methods to measure the vibration of structures are laser doppler effect, a method using GPS, and image processing technique. The method using laser doppler effect shows relatively high accuracy but uneconomical while the method using GPS requires expensive equipment, and has its signal's own error and limited speed of sampling rate. But the method using image signal is simple and economical, and is proper to get vibration of inaccessible structures and dynamic characteristics. Image signals of camera instead of sensors had been recently used by many researchers. But the existing method, which records a point of a target attached on a structure and then measures vibration using image processing technique, could have relatively the limited objects of measurement. Therefore, this study conducted shaking table test and field load test to verify the validity of the method that can measure multi-point displacement responses of structures using image processing technique.

• Korean Journal of Agricultural and Forest Meteorology
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• v.25 no.4
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• pp.337-345
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• 2023

Estimating the rice heading date is one of the most crucial agricultural tasks related to productivity. However, due to abnormal climates around the world, it is becoming increasingly challenging to estimate the rice heading date. Therefore, a more objective classification method for estimating the rice heading date is needed than the existing methods. This study, we aimed to classify the rice heading stage from various images using a CNN classification model. We collected top-view images taken from a drone and a phenotyping tower, as well as slanted-view images captured with a RGB camera. The collected images underwent preprocessing to prepare them as input data for the CNN model. The CNN architectures employed were ResNet50, InceptionV3, and VGG19, which are commonly used in image classification models. The accuracy of the models all showed an accuracy of 0.98 or higher regardless of each architecture and type of image. We also used Grad-CAM to visually check which features of the image the model looked at and classified. Then verified our model accurately measure the rice heading date in paddy fields. The rice heading date was estimated to be approximately one day apart on average in the four paddy fields. This method suggests that the water head can be estimated automatically and quantitatively when estimating the rice heading date from various paddy field monitoring images.

• Korean Journal of Remote Sensing
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• v.39 no.6_1
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• pp.1353-1369
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• 2023

In the event of a disaster accident at sea, the scale of damage will vary due to weather effects such as wind, currents, and tidal waves, and it is obligatory to minimize the scale of damage by establishing appropriate control plans through quick on-site identification. In particular, it is difficult to identify pollutants that exist in a thin film at sea surface due to their relatively low viscosity and surface tension among pollutants discharged into the sea. Therefore, this study aims to develop an algorithm to detect suspended pollutants on the sea surface in RGB images using imaging equipment that can be easily used in the field, and to evaluate the performance of the algorithm using input data obtained from actual waters. The developed algorithm uses image enhancement techniques to improve the contrast between the intensity values of pollutants and general sea surfaces, and through histogram analysis, the background threshold is found,suspended solids other than pollutants are removed, and finally pollutants are classified. In this study, a real sea test using substitute materials was performed to evaluate the performance of the developed algorithm, and most of the suspended marine pollutants were detected, but the false detection area occurred in places with strong waves. However, the detection results are about three times better than the detection method using a single threshold in the existing algorithm. Through the results of this R&D, it is expected to be useful for on-site control response activities by detecting suspended marine pollutants that were difficult to identify with the naked eye at existing sites.

• Korean Journal of Remote Sensing
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• v.39 no.6_1
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• pp.1309-1320
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• 2023

The technological development and popularization of mobile devices have developed so that users can check their location anywhere and use the Internet. However, in the case of indoors, the Internet can be used smoothly, but the global positioning system (GPS) function is difficult to use. There is an increasing need to provide real-time location information in shaded areas where GPS is not received, such as department stores, museums, conference halls, schools, and tunnels, which are indoor public places. Accordingly, research on the recent indoor positioning technology based on light detection and ranging (LiDAR) equipment is increasing to build a landmark database. Focusing on the accessibility of building a landmark database, this study attempted to develop a technique for estimating the user's location by using a single image taken of a landmark based on a mobile device and the landmark database information constructed in advance. First, a landmark database was constructed. In order to estimate the user's location only with the mobile image photographing the landmark, it is essential to detect the landmark from the mobile image, and to acquire the ground coordinates of the points with fixed characteristics from the detected landmark. In the second step, by applying the bag of words (BoW) image search technology, the landmark photographed by the mobile image among the landmark database was searched up to a similar 4th place. In the third step, one of the four candidate landmarks searched through the scale invariant feature transform (SIFT) feature point extraction technique and Homography random sample consensus(RANSAC) was selected, and at this time, filtering was performed once more based on the number of matching points through threshold setting. In the fourth step, the landmark image was projected onto the mobile image through the Homography matrix between the corresponding landmark and the mobile image to detect the area of the landmark and the corner. Finally, the user's location was estimated through the location estimation technique. As a result of analyzing the performance of the technology, the landmark search performance was measured to be about 86%. As a result of comparing the location estimation result with the user's actual ground coordinate, it was confirmed that it had a horizontal location accuracy of about 0.56 m, and it was confirmed that the user's location could be estimated with a mobile image by constructing a landmark database without separate expensive equipment.

• The Korean Journal of Nuclear Medicine Technology
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• v.19 no.2
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• pp.87-92
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• 2015

Purpose When the patients takes myocardial perfusion SPECT using $^{201}Tl$, the operator gives the patients an injection of $^{201}Tl$. But the uniformity correction map in SPECT uses $^{99m}Tc$ uniformity correction map. Thus, we want to compare the image quality when it uses $^{99m}Tc$ uniformity correction map and when it uses $^{201}Tl$ uniformity correction map. Materials and Methods Phantom study is performed. We take the data by Asan medical center daily QC condition with flood phantom including $^{201}Tl$ 21.3 kBq/mL. After postprocessing with this data, we analyze CFOV integral uniformity(I.U) and differential uniformity(D.U). And we take the data with Jaszczak ECT Phantom by American college of radiology accreditation program instruction including $^{201}Tl$ 33.4 kBq/mL. After post processing with this data, we analyze spatial Resolution, Integral Uniformity(I.U), coefficient of variation(C.V) and Contrast with Interactive data language program. Results In the flood phantom test, when it uses $^{99m}Tc$ uniformity correction map, Flood I.U is 3.6% and D.U is 3.0%. When it uses $^{201}Tl$ uniformity correction map, Flood I.U is 3.8% and D.U is 2.1%. The flood I.U is worsen about 5%, but the D.U is improved about 30% inversely. In the Jaszczak ECT phantom test, when it uses $^{99m}Tc$ uniformity correction map, SPECT I.U, C.V and contrast is 13.99%, 4.89% and 0.69. When it uses $^{201}Tl$ uniformity correction map, SPECT I.U, C.V and contrast is 11.37%, 4.79% and 0.78. All of data are improved about 18%, 2%, 13% The spatial resolution was no significant changes. Conclusion In the flood phantom test, Flood I.U is worsen but Flood D.U is improved. Therefore, it's uncertain that an image quality is improved with flood phantom test. On the other hand, SPECT I.U, C.V, Contrast are improved about 18%, 2%, 13% in the Jaszczak ECT phantom test. This study has limitations that we can't take all variables into account and study with two phantoms. We need think about things that it has a good effect when doctors decipher the nuclear medicine image and it's possible to improve the image quality using the uniformity correction map of other radionuclides other than $^{99m}Tc$, $^{201}Tl$ when we make other nuclear medicine examinations.

• The Korean Journal of Nuclear Medicine Technology
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• v.14 no.2
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• pp.117-121
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• 2010

Purpose: In nuclear medicine study, there are two methods, preset count method and preset time method, to acquire static images. We usually use preset count method for static image in $^{99m}Tc$-DMSA renal scan, but occasionally use preset time method. In case of using preset count method, we always acquire same counts but it causes a difference of scan time. In case of using preset time method, it takes same scan time to acquire images but it causes different counts. Therefore, the purpose of this study is to investigate any differences of function and formal information in both kidney by acquisition counts Materials and Methods: From January 11, 2010 to March 31, 2010, we analyzed the 30 patients (M: 11, W: 19). who were examined by $^{99m}Tc$-DMSA scan and have one side of functioning kidney relatively between 40~60%. And the patients who have cold and hot region in image were analyzed but we did not accept images of patients when it was hard to divide kidney into cortex. There was no division between subjects and age of subjects is $14.83{\pm}22.07$ old. We used the BrightView gamma camera from PHILIPS. To analyze function and formal of kidney, we used JET stream release 3.0 version from PHILIPS. Using SPSS 12.0 program, we compared descriptive statistics and paired T-test. Images were acquired sequentially in the same parameters, but there are three methods which different from acquisition time and scan time, 100 kcounts, 300 kcounts and 7 minutes method (exceed 300 kcounts). To assess function and formal information of kidney, we measured renal relative function, geometric mean and size of kidney and analyzed each difference. Results: In case of renal relative function in both kidney, 100 kcounts method was $50.52{\pm}3.64%$. 300 kcounts method was $50.38{\pm}3.66%$ and 7 minutes method was $49.91{\pm}3.40%$ and there were no statistical significant differences between each method. In case of geometric mean, 100 kcounts method was $50.08{\pm}3.25%$. 300 kcounts method was $49.89{\pm}3.40%$ and 7 minutes method was $49.91{\pm}3.24%$. And also, there were no statistical significant differences. When comparing size of kidney, 100 kcounts method was $8.23{\pm}1.96$ cm. 300 kcounts method was $8.12{\pm}1.90$ cm and 7 minutes method was $8.35{\pm}1.97$ cm. In case of right kidney, 100 kcounts method was $7.91{\pm}1.88$ cm. 300 kcounts method was $8.12{\pm}1.90$ cm and 7 minutes method was $8.25{\pm}1.96$ cm. From those values, we recognized that there were significant differences each method (p<0.05). Conclusion: From results of this study, there were no statistical differences in renal relative function and geometric mean by acquisition counts. However, in shape of kidney, the more acquisition counts are increasing, the more size of kidney is getting big. And there were statistical significant differences. Therefore, to perform reliable quantitative result, preset count method is more desirable than preset time method. Especially, in case of a follow-up test, if we use preset time method, it will cause differences of formal results in kidney due to acquisition counts each time we examine patients.

• Journal of Intelligence and Information Systems
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• v.17 no.1
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• pp.53-69
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• 2011

Vision and voice-based technologies are commonly utilized for human-robot interaction. But it is widely recognized that the performance of vision and voice-based interaction systems is deteriorated by a large margin in the real-world situations due to environmental and user variances. Human users need to be very cooperative to get reasonable performance, which significantly limits the usability of the vision and voice-based human-robot interaction technologies. As a result, touch screens are still the major medium of human-robot interaction for the real-world applications. To empower the usability of robots for various services, alternative interaction technologies should be developed to complement the problems of vision and voice-based technologies. In this paper, we propose the use of accelerometer-based gesture interface as one of the alternative technologies, because accelerometers are effective in detecting the movements of human body, while their performance is not limited by environmental contexts such as lighting conditions or camera's field-of-view. Moreover, accelerometers are widely available nowadays in many mobile devices. We tackle the problem of classifying acceleration signal patterns of 26 English alphabets, which is one of the essential repertoires for the realization of education services based on robots. Recognizing 26 English handwriting patterns based on accelerometers is a very difficult task to take over because of its large scale of pattern classes and the complexity of each pattern. The most difficult problem that has been undertaken which is similar to our problem was recognizing acceleration signal patterns of 10 handwritten digits. Most previous studies dealt with pattern sets of 8~10 simple and easily distinguishable gestures that are useful for controlling home appliances, computer applications, robots etc. Good features are essential for the success of pattern recognition. To promote the discriminative power upon complex English alphabet patterns, we extracted 'motion trajectories' out of input acceleration signal and used them as the main feature. Investigative experiments showed that classifiers based on trajectory performed 3%~5% better than those with raw features e.g. acceleration signal itself or statistical figures. To minimize the distortion of trajectories, we applied a simple but effective set of smoothing filters and band-pass filters. It is well known that acceleration patterns for the same gesture is very different among different performers. To tackle the problem, online incremental learning is applied for our system to make it adaptive to the users' distinctive motion properties. Our system is based on instance-based learning (IBL) where each training sample is memorized as a reference pattern. Brute-force incremental learning in IBL continuously accumulates reference patterns, which is a problem because it not only slows down the classification but also downgrades the recall performance. Regarding the latter phenomenon, we observed a tendency that as the number of reference patterns grows, some reference patterns contribute more to the false positive classification. Thus, we devised an algorithm for optimizing the reference pattern set based on the positive and negative contribution of each reference pattern. The algorithm is performed periodically to remove reference patterns that have a very low positive contribution or a high negative contribution. Experiments were performed on 6500 gesture patterns collected from 50 adults of 30~50 years old. Each alphabet was performed 5 times per participant using $Nintendo{(R)}$ $Wii^{TM}$ remote. Acceleration signal was sampled in 100hz on 3 axes. Mean recall rate for all the alphabets was 95.48%. Some alphabets recorded very low recall rate and exhibited very high pairwise confusion rate. Major confusion pairs are D(88%) and P(74%), I(81%) and U(75%), N(88%) and W(100%). Though W was recalled perfectly, it contributed much to the false positive classification of N. By comparison with major previous results from VTT (96% for 8 control gestures), CMU (97% for 10 control gestures) and Samsung Electronics(97% for 10 digits and a control gesture), we could find that the performance of our system is superior regarding the number of pattern classes and the complexity of patterns. Using our gesture interaction system, we conducted 2 case studies of robot-based edutainment services. The services were implemented on various robot platforms and mobile devices including $iPhone^{TM}$. The participating children exhibited improved concentration and active reaction on the service with our gesture interface. To prove the effectiveness of our gesture interface, a test was taken by the children after experiencing an English teaching service. The test result showed that those who played with the gesture interface-based robot content marked 10% better score than those with conventional teaching. We conclude that the accelerometer-based gesture interface is a promising technology for flourishing real-world robot-based services and content by complementing the limits of today's conventional interfaces e.g. touch screen, vision and voice.

• Journal of Dental Rehabilitation and Applied Science
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• v.26 no.1
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• pp.21-32
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• 2010

The convergence angle of a prepared tooth is a very important factor in the retention and resistance of a crown restoration. But various intraoral environments and clinician's techniques make it difficult to obtain the ideal inclination. Therefore, in this study, clinical convergence angle of a prepared tooth was investigated. The data was collected from the patient models of prosthodontic residents and the patient models of general practitioners. The images of mesiodistal and buccolingual surfaces were taken with a digital camera to evaluate the convergence angle on 'ImageJ' program. The images were classified according to the criteria (1. Clinician group, 2. Position in the dental arch, 3. The purpose of abutment preparation)and then analyzed. The mean convergence angle of a prepared tooth for Korean clinicians was $15.02^{\circ}$ (${\pm}10.13^{\circ}$). 1. It was significant in the convergence angle between the general practitioner group and the prosthodontic resident group(p<0.05). 2. It was significant between the mesiodistal and buccolingual surface in the the prosthodontic resident group(p<0.05). 3. For the general practitioner group, it was significant when anteriors and premolars were compared with molars(p<0.05). For the prosthodontic resident group, it was significant when anteriors and premolars were compared with molars (p<0.05). 4. When divided into upper and lower arches, for the general practitioner group, it showed significant difference in the buccolingual aspect(p<0.05). Also in the prosthodontic resident group, it showed significant difference in the buccolingual aspect(p<0.05). 5. Dividing left and right sides of the arches, there was no significant difference in the general practitioner group and the prosthodontic resident group(p>0.05). 6. In the general practitioner group, it was significant in the mesiodistal axial convergence angle of single crown abutment and 3 unit bridge abutment(p<0.05). In the prosthodontic resident group, it was significant in the mesiodistal and overall axial convergence angle of single crown abutment and 3 unit bridge abutment(p<0.05). Clinical convergence angle of prepared tooth in Korea was included in agreement with other studies investigating convergence angle that ranged from 10 to 22 degrees, achieved in clinical practice.