• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.10 no.6
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• pp.609-616
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• 2017

In this paper, we propose an algorithm to obtain more stable and high recognition rate by using left and right rotation information of input image in order to obtain a stable recognition rate in face recognition. The proposed algorithm uses the facial image as the input information in the web camera environment to reduce the size of the image and normalize the information about the brightness and color to obtain the improved recognition rate. We apply Principal Component Analysis (PCA) to the detected candidate regions to obtain feature vectors and classify faces. Also, In order to reduce the error rate range of the recognition rate, a set of data with the left and right $45^{\circ}$ rotation information is constructed considering the directionality of the input face image, and each feature vector is obtained with PCA. In order to obtain a stable recognition rate with the obtained feature vector, it is after scattered in the eigenspace and the final face is recognized by comparing euclidean distant distances to each feature. The PCA-based feature vector is low-dimensional data, but there is no problem in expressing the face, and the recognition speed can be fast because of the small amount of calculation. The method proposed in this paper can improve the safety and accuracy of recognition and recognition rate faster than other algorithms, and can be used for real-time recognition system.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.12 no.2
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• pp.162-169
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• 2019

Non-destructive freshness measurement using spectroscopy has been carried out several times, but research on freshness and freshness has not been conducted. Therefore the purpose of this study is to develop a system for visually measuring and quantifying the air sack inside the egg by non - destructive method. The experimental environment which designed a small chamber was composed of 850nm band of two IR lasers, IR camera and two servo motors to acquire air sack Images. When the air sack volume ratio is 2.9% or less and the density is 0.9800 or more, the Haugh Unit value is 60 or more It was judged to be a fresh egg of a grade B or higher. These results mean, using the weight measurement, nondestructive decision system, and freshness evaluating algorithm. It can be expected to distinguish grade B or more marketable eggs without using destructive methods.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.3
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• pp.587-593
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• 2019

The field of geospatial information is rapidly changing due to the development of sensor and data processing technology that can acquire location information. And demand is increasing in various related industries and social activities. The construction and utilization of three dimensional geospatial information that is easy to understand and easy to understand can be an essential element to improve the quality and reliability of related services. In recent years, 3D laser scanners are widely used as 3D geospatial information construction technology. However, 3D laser scanners may cause shadow areas where data acquisition is not possible when objects are large in size or complex in shape. In this study, 3D model of an object has been created by acquiring oblique images using an unmanned aerial vehicle and processing the data. The study area was selected, oblique images were acquired using an unmanned aerial vehicle, and point cloud type 3D model with 0.02 m spacing was created through data processing. The accuracy of the 3D model was 0.19m and the average was 0.11m. In the future, if accuracy is evaluated according to shooting and data processing methods, and 3D model construction and accuracy evaluation and analysis according to camera types are performed, the accuracy of the 3D model will be improved. In the point cloud type 3D model, Cross section generation, drawing of objects, and so on, it is possible to improve work efficiency of spatial information service and related work.

• The Journal of Korean Institute of Information Technology
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• v.16 no.11
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• pp.51-59
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• 2018

The Multi-Mission Unmanned Surface Vehicle(MMUSV), which is manufactured using glass Fiber Reinforced Plastic(FRP) material, is designed to perform a surveillance and reconnaissance on the sea. Various navigation sensors, such as RADAR, RIDAR, camera, are mounted on a mast to perform an autonomous navigation. And a dummy gun is mounted on the deck of the MMUSV for a target tracking and disposal. It is necessary to analyze a strength for structures mounted on the deck because the MMUSV performs missions under a severe sea state. In this paper, a strength analysis of the mast structure is performed on static loads and lateral external loads to verify an adequacy of the designed mast through a series of simulations. Based on the results of captive model tests, a strength analysis for a heave motion of the mast structure is conducted using a simulation tool. Also a simulation and fatigue test for a mounting part between the MMUSV and the dummy gun are performed using a specimen. The simulation and test results are represented that a structure of the mast and mounting part of the dummy gun are appropriately designed.he impact amount are performed through simulation and experiments.

• Journal of the Society of Disaster Information
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• v.14 no.4
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• pp.501-509
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• 2018

Purpose: UAV-based photo measurements are being researched using UAVs in the space information field as they are not only cost-effective compared to conventional aerial imaging but also easy to obtain high-resolution data on desired time and location. In this study, the UAV-based high-resolution images were used to perform the land cover classification. Method: RGB cameras were used to obtain high-resolution images, and in addition, multi-distribution cameras were used to photograph the same regions in order to accurately classify the feeding areas. Finally, Land cover classification was carried out for a total of seven classes using created ortho image by RGB and multispectral camera, DSM(Digital Surface Model), NDVI(Normalized Difference Vegetation Index), GLCM(Gray-Level Co-occurrence Matrix) using RF (Random Forest), a representative supervisory classification system. Results: To assess the accuracy of the classification, an accuracy assessment based on the error matrix was conducted, and the accuracy assessment results were verified that the proposed method could effectively classify classes in the region by comparing with the supervisory results using RGB images only. Conclusion: In case of adding orthoimage, multispectral image, NDVI and GLCM proposed in this study, accuracy was higher than that of conventional orthoimage. Future research will attempt to improve classification accuracy through the development of additional input data.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.2
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• pp.766-773
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• 2021

Chemicals, such as ammunition, are disposable items that cannot be reused because of their operational characteristics. The reliability of the test process and test results are important factors in evaluating the performance of guns and ammunition. The pressure after firing is a crucial value in an acceptance test of guns and ammunition performance; hence, accurate measurements are required. The pressure in the artillery is measured using the copper crusher gauge. The compression amount of copper is converted into a pressure by either a length-pressure conversion table or conversion formula. Therefore, the exact measurement of the squeeze of the copper crusher is related directly to the correct estimate of the pressure. Currently, the pressure is measured manually by the operator, which always includes some human error. In this study, the cause of the measurement error was analyzed, and the automatic measuring system for copper crusher deformation was developed to minimize the error elements. A copper crusher could be measured using the probe sensor and CCD camera, and the Jig for stable positioning was also designed. A designated SW was also developed for the system operating and measurement-analysis. This measuring system through this study may be used for an ammunition stockpile reliability test and gun/ammunition acceptance test.

• The Journal of the Convergence on Culture Technology
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• v.7 no.3
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• pp.553-564
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• 2021

This study analyzed the the risk of halogen lamp for pigsty heating and its fire prevention. Halogen lamps are used for keeping warm in pen because of their excellent economy and convenience. However, there is a high risk of fire due to poor safety management and exposure to animal movements. In fact, after exploring old pigsty and cattle shed, it was easy to confirm that they were exposed to fire risks. We noted this point and studied the possibility of fire by experiment due to combustible contact with halogen lamp and carelessness in use. The experiment was conducted under conditions similar to the actual use environment. After installing halogen lamps to the height used in actual pen, the temperature change was observed with infrared camera with straw, sawdust and rice husks on the floor. And assuming abnormal conditions, the experiment was also conducted under conditions the lamp dropped on the floor or combustible material came into contact with the glass tube inside the lamp. If halogen lamps were used in normal condition, there was no risk of fire. However, in abnormal use environments, smoke comes out or even ignited. Even if it is convenient for use or highly utilized, high risk of fire will require setting up fire prevention measures or regulation of use. Through in-depth fire investigation and research, we should promote the risk of fire and make efforts to prevent fire to minimize human life and property damage.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.19 no.6
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• pp.96-106
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• 2020

To solve the limitation of traffic monitoring that occur from embedded sensor such as loop and piezo sensors, the thermal imaging camera was installed on the roadside. As the length of Class 1(passenger car) is getting longer, it is becoming difficult to classify from Class 3(2-axle truck) by using an embedded sensor. The collected images were labeled to generate training data. A total of 17,536 vehicle images (640x480 pixels) training data were produced. CNN (Convolutional Neural Network) was used to achieve vehicle classification based on thermal image. Based on the limited data volume and quality, a classification accuracy of 97.7% was achieved. It shows the possibility of traffic monitoring system based on AI. If more learning data is collected in the future, 12-class classification will be possible. Also, AI-based traffic monitoring will be able to classify not only 12-class, but also new various class such as eco-friendly vehicles, vehicle in violation, motorcycles, etc. Which can be used as statistical data for national policy, research, and industry.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.15 no.2
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• pp.103-108
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• 2022

Various studies have been conducted on cloud observation using all-sky images acquired with a wide-angle camera system since the early 21st century, but it is judged that an automatic observation system that can completely replace the eye observation has not been obtained. In this study, to verify the quantification of cloud observation, which is the final step of the algorithm proposed to automate the observation, the cloud distribution of the all-sky image and the corrected image were compared and analyzed. The reason is that clouds are formed at a certain height depending on the type, but like the retina image, the center of the lens is enlarged and the edges are reduced, but the effect of human learning ability and spatial awareness on cloud observation is unknown. As a result of this study, the average cloud observation error of the all-sky image and the corrected image was 1.23%. Therefore, when compared with the eye observation in the decile, the error due to correction is 1.23% of the observed amount, which is very less than the allowable error of the eye observation, and it does not include human error, so it is possible to collect accurately quantified data. Since the change in cloudiness due to the correction is insignificant, it was confirmed that accurate observations can be obtained even by omitting the unnecessary correction step and observing the cloudiness in the pre-correction image.

• Journal of the Society of Cosmetic Scientists of Korea
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• v.48 no.2
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• pp.87-95
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• 2022

This study is about the development of transparent cleansing water with one of the beta-hydroxy acids (BHA), salicylic acid, and capryloyl salicylic acid, which is one of the lipo-hydroxy acids (LHA). Transparent appearance was stabilized by increasing the solubility of lipophilic salicylic acid and capryloyl salicylic acid in water using ethanol, polyol, and sodium hydroxide, and supplementing suspension and deposition using a double micelle structure of two types of PEG surfactants. Cleansing water applied with this technology was developed, and makeup removing ability and skin texture improvement ability were confirmed using an optical camera and an image analyzer. This solubilization technology is proposed as a new approach of LHA, which has been difficult to apply due to its low solubility in water, and is expected to help in the development of new chemical peeling products.