• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.1
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• pp.42-50
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• 2016

Recently, researches about the communication between LED array and the camera (alias 'Visual-MIMO'), have been actively conducted, and the application to the vehicle and a smart phone is expected to be maximized. Since the bit error may occur if the ISI is severe in a LED array, it is necessary to switch from the multiplexing to the diversity mode. In this paper, according to the use or not of a reference array pattern, a method for determining the transition time to the diversity mode is suggested and verified. When using the reference pattern, it determines the transition time to the diversity mode from the multiplexing using the brightness information of the received image. If the reference array pattern is not used, the size of LED array compared to the entire image according to the distance is used and the size of the LED array at the distance of a severe ISI may be used for the determination of transition time to the diversity. Finally, the proposed method is verified through the simulation and hardware experiments as well as by analyzing the performance in accordance with the ISI level and the distance.

• Journal of Korean Society for Quality Management
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• v.48 no.4
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• pp.581-596
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• 2020

Purpose: purpose of this study was to propose the web application platform which can be to detect and discriminate various diseases and pest of tomato plant based on the large amount of disease image data observed in the facility or the open field. Methods: The deep learning algorithms uesed at the web applivation platform are consisted as the combining form of Faster R-CNN with the pre-trained convolution neural network (CNN) models such as SSD_mobilenet v1, Inception v2, Resnet50 and Resnet101 models. To evaluate the superiority of the newly proposed web application platform, we collected 850 images of four diseases such as Bacterial cankers, Late blight, Leaf miners, and Powdery mildew that occur the most frequent in tomato plants. Of these, 750 were used to learn the algorithm, and the remaining 100 images were used to evaluate the algorithm. Results: From the experiments, the deep learning algorithm combining Faster R-CNN with SSD_mobilnet v1, Inception v2, Resnet50, and Restnet101 showed detection accuracy of 31.0%, 87.7%, 84.4%, and 90.8% respectively. Finally, we constructed a web application platform that can detect and discriminate various tomato deseases using best deep learning algorithm. If farmers uploaded image captured by their digital cameras such as smart phone camera or DSLR (Digital Single Lens Reflex) camera, then they can receive an information for detection, identification and disease control about captured tomato disease through the proposed web application platform. Conclusion: Incheon Port needs to act actively paying.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.2
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• pp.21-27
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• 2023

This paper is a study on the development of an app that assists in putting alignment in golf. The proposed app measures the position and size of the hole cup on the green to provide the distance between the hole cup and the aiming point. To achieve this, artificial intelligence object recognition technology was applied in the development process. The app measures the position and size of the hole cup in real-time using object recognition technology on the camera image of the smartphone. The app then displays the distance between the aiming point and the hole cup on the camera image to assist in putting alignment. The proposed app was developed for iOS on the iPhone. Performance testing of the developed app showed that it could sufficiently recognize the hole cup in real-time and accurately display the distance to provide helpful information for putting alignment.

• Journal of Korea Society of Industrial Information Systems
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• v.14 no.4
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• pp.101-115
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• 2009

This study analyzed the diffusion process of digital convergence products focused on camera phon to compare the traditional adoption-diffusion model with use-diffusion model proposed by Shih and Venkatesh(2004). The results suggested that observability, perceived usefulness, innovativeness, relative advantage have effects on the intention of repurchase in the adoption-diffusion model. On the other hand, the intention of repurchase has been affected by technological sophistication, satisfaction, innovativeness, relative advantage in the use-diffusion model. These results imply that the traditional adoption-diffusion model could be applied to the cases of the digital convergence products. In addition, the results also show that the use-diffusion model is superior to the traditional model in analyzing the diffusion of digital convergence products.

• Journal of Fashion Business
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• v.27 no.2
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• pp.26-38
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• 2023

This study aimed to develop a visually differentiated quarantine suit design for giving 119 paramedics comfort to work and psychological stability and to awaken awareness without fear or pressure of the public through literature review and practical research. Basic research was conducted on firefighting uniforms and quarantine suits in Korea and abroad, focusing on domestic and foreign related literature. An interview survey was conducted to identify the current status, problems, and preferences of the design. Research subjects were eight dispatched paramedics and two executives in Seoul and Gwangju. The survey period was from September 15, 2022 to October 10, 2022. Interviews were conducted through phone calls. Results of this study were as follows. Most of the quarantine suits currently worn were Level D style ready-made clothes without coverall patterns. The current quarantine suit was designed without reflecting the symbolism of the National Fire Agency. They were wearing a generous size without having to think about the fit. Most of these quarantine suits were white. In addition, the quarantine suit could not be equipped with a camera for the safety of paramedics. After identifying improvements based on results of the above interview analysis, the following quarantine suit design was proposed. First, it would be differentiated from other institutions by designing suits with symbolism. Second, the convenience of size, camera equipment, and better breathability and style than Level D should be considered. Based on these results, a total of five quarantine suits were designed.

• Journal of Korea Water Resources Association
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• v.49 no.6
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• pp.469-480
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• 2016

The present study aims to develop a real-time surface image velocimeter (SIV) using an Android smartphone. It can measure river surface velocity by using its built-in sensors and processors. At first the SIV system figures out the location of the site using the GPS of the phone. It also measures the angles (pitch and roll) of the device by using its orientation sensors to determine the coordinate transform from the real world coordinates to image coordinates. The only parameter to be entered is the height of the phone from the water surface. After setting, the camera of the phone takes a series of images. With the help of OpenCV, and open source computer vision library, we split the frames of the video and analyzed the image frames to get the water surface velocity field. The image processing algorithm, similar to the traditional STIV (Spatio-Temporal Image Velocimeter), was based on a correlation analysis of spatio-temporal images. The SIV system can measure instantaneous velocity field (1 second averaged velocity field) once every 11 seconds. Averaging this instantaneous velocity measurement for sufficient amount of time, we can get an average velocity field. A series of tests performed in an experimental flume showed that the measurement system developed was greatly effective and convenient. The measured results by the system showed a maximum error of 13.9 % and average error less than 10 %, when we compared with the measurements by a traditional propeller velocimeter.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.14 no.2
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• pp.93-98
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• 2015

This study focuses on simulation technology in the injection molding process for plastic optic lenses. The CAE program 3D TIMON was used to predict retardation, flow patterns and warpage deformation. The results were compared to the results of optic lenses as measured using the WPA-100 retardation measurement device with injection molding CAE for retardation predictions. According to the analysis and measured results, the distributions of retardation between the CAE results and the measurement results were similar. It was also confirmed that varying the injection speed had an effect on the injection pressure, warpage deformation and retardation distribution. As the injection speed increases, the injection pressure also increases and warpage deformation decreases. However, as the injection speed increases, the retardation distribution deteriorates.

• Journal of the Korean Society for Precision Engineering
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• v.31 no.7
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• pp.561-567
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• 2014

Precision injection mold is an essential element in order to manufacture small and precision plastic lenses used for phone camera. There are many critical factors to meet the requested specifications of high quality plastic lenses. One of the main issues to realize high quality is minimizing decenter value, which becomes more critical as pixel numbers increases. This study suggests the method to minimize decenter value by modifying ejecting structure of the mold. Decenter value of injection-molded lens decreased to 1 ${\mu}m$ level from 5 ${\mu}m$ by applying suggested ejecting method. Also, we also developed BIS (Built-in Sensor) based smart mold system, which has pressure and temperature sensors inside of the mold. Pressure and temperature profiles from cavities are obtained and can be used for deduction of optimal injection molding condition, filling imbalance evaluation, status monitoring of injection molding and prediction of lens quality.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.46 no.9
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• pp.39-48
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• 2009

Human face tracking has gradually become an important issue in applications for portable multimedia devices such as digital camcorder, digital still camera and cell phone. Current embedded face tracking software implementations lack the processing abilities to track faces in real time mobile video processing. In this paper, we propose a power efficient hardware-based face tracking architecture operating in real time. The proposed system was verified by FPGA prototyping and ASIC implementation using Samsung 65nm CMOS process. The implementation result shows that tracking speed is less than 8.4 msec with 150K gates and 20 mW average power consumption. Consequently it is validated that the proposed system is adequate for portable multimedia device.

• Journal of Korea Society of Industrial Information Systems
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• v.20 no.2
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• pp.45-56
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• 2015

In this paper we propose a very rapid moving object tracking method for an object-based auto focus on a smart phone camera. By considering the limit of non-learning approach on low-performance platforms, we use a sliding-window detection technique based on histogram features. By adapting the integral histogram, we solve the problem of the time-consuming histogram computation on each sub-window. For more speed up, we propose a local candidate search, and an adaptive scaling template method. In addition, we propose to apply a stabilization term in the matching function for a stable detection location. In experiments on our dataset, we demonstrated that we achieved a very rapid tracking performance demonstrating over 100 frames per second on a PC environment.