• Journal of Korea Society of Industrial Information Systems
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• v.13 no.1
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• pp.11-21
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• 2008

Recently, it has shown an increased interest in 3D stereoscopic contents due to the development of the digital image media. Therefore, many techniques in 3D stereoscopic image generation have being researched and developed. However, it is difficult to generate high immersion and natural 3D stereoscopic contents, because the lack of 3D geometric information imposes restrictions in 2D image. In addition, control of the camera interval and rendering of the both eyes must be repetitively accomplished for the stereo effect being high. Therefore, we propose integrated editing system for 3D stereoscopic contents production using a variety of images. Then we generate 3D model from projective geometric information in single 2D image using image-based modeling method. And we offer real-time interactive 3D stereoscopic preview function for determining high immersion 3D stereo view. And then we generate intuitively 3D stereoscopic contents of high-quality through a stereoscopic LCD monitor and a polarizing filter glasses.

• Journal of the Korea institute for structural maintenance and inspection
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• v.16 no.2
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• pp.40-48
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• 2012

Steel corrosion in concrete is a main cause of deterioration and early failure of concrete structures. A novel integration of electromagnetic heat induction and infrared (IR) thermography is proposed for nondestructive detection of steel corrosion in concrete, by taking advantage of the difference in thermal characteristics of corroded and non-corroded steel. This paper focuses on experimental investigation of the concept. An inductive heater is developed to remotely heat the embedded steel from concrete surface, which is integrated with an IR camera. Concrete samples with different cover depths are prepared. Each sample is embedded with a single rebar in the middle, resulting an identical cover depth from the front and the back surfaces, which enable heat induction from one surface and IR imaging from the other simultaneously. The impressed current (IC) method is adopted to induce accelerated corrosion on the rebar. IR video images are recorded during the entire heating and cooling periods. The test results demonstrate a clear difference in thermal characteristics between corroded and non-corroded samples. The corroded sample shows higher rates of heating and cooling than those of the non-corroded sample. This study demonstrates a potential for nondestructive detection of rebar corrosion in concrete.

• Journal of the Korean Institute of Intelligent Systems
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• v.20 no.4
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• pp.580-585
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• 2010

In this paper, The object Tracking System is designed by SOPC based Nios II embedded processor and C2H compiler. And this system using single PTZ camera can effectively control IPs in the platform of SOPC based Nios II Embedded Processor and creating IP by C2H(C-To-Hardware) compiler for image-in/output, image-processing and devices of communication that can supply various monitoring information to network or serial. Accordingly, Special quality and processing speed of object tracking using high-quality algorism in the system is improved by hardware/software programming methods.

• Journal of the Korea Convergence Society
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• v.12 no.10
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• pp.1-8
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• 2021

In online meetings and classes using webcams, the chromakey technique is a very necessary part to produce content. We proposed a technology that enables background synthesis without using a cloth for chromakey. The proposed method consists of three steps: an HSI image conversion step, a step of detecting a region changed from a background, and a step of replacing the background region with a chromakey and applying it. In the input video, the block average image of each frame is calculated, and the difference between the block average image of the background image and the block average image of the input image is used to detect the change area. The developed chromakey effect technology uses a technique of acquiring a background image without an object from a single camera and extracting only an object by distinguishing the moving object and the background. The proposed method is not only capable of processing even if the background has a variety of colors, but also has the seamless processing of the boundary lines of objects.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.7
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• pp.962-970
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• 2021

The cause of the majority of vehicle accidents is a safety issue due to the driver's inattention, such as drowsy driving. A forward collision warning system (FCWS) can significantly reduce the number and severity of accidents by detecting the risk of collision with vehicles in front and providing an advanced warning signal to the driver. This paper describes a low power embedded system based FCWS for safety. The algorithm computes time to collision (TTC) through detection, tracking, distance calculation for the vehicle ahead and current vehicle speed information with a single camera. Additionally, in order to operate in real time even in a low-performance embedded system, an optimization technique in the program with high and low levels will be introduced. The system has been tested through the driving video of the vehicle in the embedded system. As a result of using the optimization technique, the execution time was about 170 times faster than that when using the previous non-optimized process.

• Advances in Computational Design
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• v.4 no.2
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• pp.73-90
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• 2019

The growth in the number of single-member households is a critical issue worldwide, especially among the elderly. For those living alone, who may be unaware of their health status or routines that could improve their health, a continuous healthcare monitoring system could provide valuable feedback. Assessing the performance adequacy of activities of daily living (ADL) can serve as a measure of an individual's health status; previous research has focused on determining a person's daily activities and extracting the most frequently performed behavioral patterns using camera recordings or wearable sensing techniques. However, existing methods used to extract common patterns of an occupant's activities in the home fail to address the spatio-temporal dimensions of human activities simultaneously. Though multiple sequence alignment (MSA) offers some advantages - such as inherent containment of the spatio-temporal data in sequence format, and rapid identification of hidden patterns - MSA has rarely been used to extract in-home ADL routines. This research proposes a method to extract a household occupant's ADL routines from a cumulative spatio-temporal data log of occupancy collected using a non-intrusive method (i.e., a tomographic motion detection system). The findings from an occupant's 28-day spatio-temporal activity log demonstrate the capacity of the proposed approach to identify routine patterns of an occupant's daily activities and to reveal the order, duration, and frequency of routine activities. Routine ADL patterns identified from the proposed approach are expected to provide a basis for detecting/evaluating abrupt or gradual changes of an occupant's ADL patterns that result from a physical or mental disorder, and can offer valuable information for home automation applications by enabling the prediction of ADL patterns.

• Journal of the Korean Society of Safety
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• v.34 no.1
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• pp.40-44
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• 2019

Experimental studies have been carried out to investigate characteristics of gas explosion using a multi layered water gel barrier in a vented explosion chamber. The chamber is consisted of 1600 mm in length, with a square cross-section of $100{\times}100mm^2$. The gel concentration of inner layer of MLWGB ranged from 10% to 90% with intervals of 10% by weight of gel. Displacement of the MLWGB was photographed with a measured using a high-speed video camera, and pressure development was measured using a data acquisition system. It was found that MLWGBs with 10 ~ 20% inner layer concentrations were ruptured during the explosions. As the concentrations of inner layer increased from 30% to 90%, the barriers were not ruptured. As the gel concentrations of the inner layer increased, the displacement increased toward the chamber exit and the pressure decreased for the ruptured barriers. It was found that the pressure attenuation obtained from the MLWGB was higher than that of the single water gel barrier. For the cases of non-ruptured barriers, the pressure inside the chamber less increased with increasing gel concentrations of the inner layer. It was also found that the displacement moved back into the chamber for non-ruptured MLWGBs, and it was sensitive to the gel concentrations.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.10
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• pp.3858-3874
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• 2021

As an essential part of the urban transportation system, precise perception of the traffic flow parameters at the traffic signal intersection ensures traffic safety and fully improves the intersection's capacity. Traditional detection methods of road traffic flow parameter can be divided into the micro and the macro. The microscopic detection methods include geomagnetic induction coil technology, aerial detection technology based on the unmanned aerial vehicles (UAV) and camera video detection technology based on the fixed scene. The macroscopic detection methods include floating car data analysis technology. All the above methods have their advantages and disadvantages. Recently, indoor location methods based on wireless signals have attracted wide attention due to their applicability and low cost. This paper extends the wireless signal indoor location method to the outdoor intersection scene for traffic flow parameter estimation. In this paper, the detection scene is constructed at the intersection based on the received signal strength indication (RSSI) ranging technology extracted from the wireless signal. We extracted the RSSI data from the wireless signals sent to the road side unit (RSU) by the vehicle nodes, calibrated the RSSI ranging model, and finally obtained the traffic flow parameters of the intersection entrance road. We measured the average speed of traffic flow through multiple simulation experiments, the trajectory of traffic flow, and the spatiotemporal map at a single intersection inlet. Finally, we obtained the queue length of the inlet lane at the intersection. The simulation results of the experiment show that the RSSI ranging positioning method based on wireless signals can accurately estimate the traffic flow parameters at the intersection, which also provides a foundation for accurately estimating the traffic flow state in the future era of the Internet of Vehicles.

• Korean Journal of Agricultural Science
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• v.47 no.4
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• pp.1109-1122
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• 2020

The aim of this study was to develop a marbling classification and prediction model using small parts of sirloin images based on a deep learning algorithm, namely, a convolutional neural network (CNN). Samples were purchased from a commercial slaughterhouse in Korea, images for each grade were acquired, and the total images (n = 500) were assigned according to their grade number: 1++, 1+, 1, and both 2 & 3. The image acquisition system consists of a DSLR camera with a polarization filter to remove diffusive reflectance and two light sources (55 W). To correct the distorted original images, a radial correction algorithm was implemented. Color images of sirloins of Hanwoo (mixed with feeder cattle, steer, and calf) were divided and sub-images with image sizes of 161 × 161 were made to train the marbling prediction model. In this study, the convolutional neural network (CNN) has four convolution layers and yields prediction results in accordance with marbling grades (1++, 1+, 1, and 2&3). Every single layer uses a rectified linear unit (ReLU) function as an activation function and max-pooling is used for extracting the edge between fat and muscle and reducing the variance of the data. Prediction accuracy was measured using an accuracy and kappa coefficient from a confusion matrix. We summed the prediction of sub-images and determined the total average prediction accuracy. Training accuracy was 100% and the test accuracy was 86%, indicating comparably good performance using the CNN. This study provides classification potential for predicting the marbling grade using color images and a convolutional neural network algorithm.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.20 no.6
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• pp.115-121
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• 2020

With the spread of IoT technology, various IoT applications using facial recognition are emerging. This paper describes the design and implementation of a remote control system using deep learning-based face recognition and hand gesture recognition. In general, an application system using face recognition consists of a part that takes an image in real time from a camera, a part that recognizes a face from the image, and a part that utilizes the recognized result. Raspberry PI, a single board computer that can be mounted anywhere, has been used to shoot images in real time, and face recognition software has been developed using tensorflow's FaceNet model for server computers and hand gesture recognition software using OpenCV. We classified users into three groups: Known users, Danger users, and Unknown users, and designed and implemented an application that opens automatic door locks only for Known users who have passed both face recognition and hand gestures.