• The Journal of Korean Institute of Information Technology
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• v.17 no.8
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• pp.11-19
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• 2019

Against advanced image-related crimes, a high level of digital forensic methods is required. However, feature-based methods are difficult to respond to new device features by utilizing human-designed features, and deep learning-based methods should improve accuracy. This paper proposes a deep learning model to identify camera models based on DenseNet, the recent technology in the deep learning model field. To extract camera sensor features, a HPF feature extraction filter was applied. For camera model identification, we modified the number of hierarchical iterations and eliminated the Bottleneck layer and compression processing used to reduce computation. The proposed model was analyzed using the Dresden database and achieved an accuracy of 99.65% for 14 camera models. We achieved higher accuracy than previous studies and overcome their disadvantages with low accuracy for the same manufacturer.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.2
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• pp.221-227
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• 2021

Recently, interests in mask-type skin care devices using light-emitting diodes have been increasing and optical stimuli at certain wavelengths have been known to have various therapeutic effects, such as skin whitening, acne treatment, elasticity and wrinkle improvement by controlling the exposure to wavelengths of light and irradiation time. In particular, light sources of different wavelengths are applied in masks for the purpose of suppressing skin aging, inducing cell proliferation, and alleviating skin inflammation. In this paper, we developed a light-emitting diode control system that is actively used in skin regeneration masks using a microcontroller. Optical stimuli with different manners were applied to skin fibroblast cells in a single or complex wavelengths, and then confirmed how they are effective in the cell differentiation. In addition, we found a specific wavelength that has a positive effect on cell proliferation rates, and confirm the effectiveness of cell proliferation by image processing based quantitative analysis.

• Journal of Biomedical Engineering Research
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• v.43 no.5
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• pp.361-368
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• 2022

The purpose of this study was to develop a hand rehabilitation training system for hemiplegic patients. We also tried to find out five hand postures (WF: Wrist Flexion, WE: Wrist Extension, BG: Ball Grip, HG: Hook Grip, RE: Rest) in real-time using multi-channel EMG-based deep learning. We performed a pre-processing method that converts to Spider Chart image data for the classification of hand movement from five test subjects (total 1,500 data sets) using Convolution Neural Networks (CNN) deep learning with an 8-channel armband. As a result of this study, the recognition accuracy was 92% for WF, 94% for WE, 76% for BG, 82% for HG, and 88% for RE. Also, ten physical therapists participated for the usability evaluation. The questionnaire consisted of 7 items of acceptance, interest, and satisfaction, and the mean and standard deviation were calculated by dividing each into a 5-point scale. As a result, high scores were obtained in immersion and interest in game (4.6±0.43), convenience of the device (4.9±0.30), and satisfaction after treatment (4.1±0.48). On the other hand, Conformity of intention for treatment (3.90±0.49) was relatively low. This is thought to be because the game play may be difficult depending on the degree of spasticity of the hemiplegic patient, and compensation may occur in patient with weakened target muscles. Therefore, it is necessary to develop a rehabilitation program suitable for the degree of disability of the patient.

• Journal of the Korea Society of Computer and Information
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• v.29 no.5
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• pp.67-74
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• 2024

As the number of coffee shops increases, many people are studying or working at coffee shops. Coffee shop operators have been required to analyze customer visits due to customer turnover and profit problems. Methods such as image analysis, QR code authentication, and Bluetooth beacon have been proposed for these statistics and analysis. However, it is difficult to use due to problems such as invasion of privacy and low accuracy. Therefore, in this study, to solve these problem and provide more accurate in-store congestion information, we propose a crowding measurement method of coffee shop using high frequency signal. There is an advantage in that a high frequency signal replaces the Bluetooth signal, and the transmission range of the signal is limited to the store, thereby increasing the accuracy of the method. To verify the performance of the proposed system, we conducted a comparative experiment with a Bluetooth based system, and as a result, the proposed method showed lower misrecognition rate. Thus, the proposed method will be an effective useful service for providing information on crowding at coffee shops and processing statistics.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.48 no.3
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• pp.50-61
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• 2011

The Infrared touch method is generally used for a mid and large-size touch screen. But this method has several problems, such as difficulty with installation of a touch-object recognition device, limited application and coordinate error in multi-point touch system. Since we can take advantages of both color and local information when we use general cameras for a touch screen, a touch screen using general camera is more efficient than infrared one. It also has an advantage of easy installation of a touch-object device. However, it did not much appeal in a market because of several problems, such as color sensitivity, illumination and reflected light. In this paper, we study a method for a touch screen using a general camera and image processing method to recognize touch objects and coordinate calculation method to single and multi-point touch screen. It has the same recognition performance as an infrared touch screen for single-point method. And it does not have ghost point problem by using distance information of touch object and camera in multi-point touch system. But recognition performances of multi-point touch screen are less than single-point. If we improve execution time, this method can replace an infrared method for a single point touch screen, according to result of experience.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.30 no.3
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• pp.229-235
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• 2019

The implementation of an in-band full-duplex wireless communication system is demonstrated in this study. In the analog/RF domain, the self-interference(SI) signal is reduced using a separate antenna for the transmitter and receiver paths, and most of the SI signal is canceled in the digital domain. A software defined radio(SDR) is used to implement the in-band full-duplex wireless communication system. The USRP X310 device uses transmitting and receiving antennas. By adjusting the gain of the transmitting and receiving ends of the SDR device, the magnitude of the SI signal entering the receiving antenna, and the size of the received signal from the outside, are both set to -64 dB. To verify the in-band full-duplex wireless communication performance, the source data is image and orthogonal frequency-division multiplexing is used for modulation. A WiFi standard frame with a carrier frequency of 2.67 GHz and bandwidth of 20 MHz is used. In the received signal, the SI signal is canceled by digital signal processing and the SI signal is attenuated by up to 34 dB. OFDM demodulation was impossible when the SI signal was not removed. However, the bit error rate is reduced to $2.63{\times}10^{-5}$ when the SI signal is attenuated by 34 dB, and no error is detected in the 100 Mbit data output as a result of passing through the Viterbi decoder.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.16 no.1
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• pp.43-53
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• 2016

In this study, under the assumption that there may be differences in colour attributes that can be perceived according to the brightness of the background and the size of the colour stimulus, a test was conducted where colour matching was done for stimulus sizes of $10^{\circ}$ and $20^{\circ}$ in terms of peripheral vision by varying the background brightness. The test results showed that depending on the background brightness and the specific combinations of the Munsell colour attributes used as the test stimulus, colours can be perceived differently even if they are the same colours. In addition, in contrast to findings from previous studies on colour perception according to the stimulus size, it was found that even if the size of the colour stimulus is relatively small, colours can be perceived more colourfully or more brightly with changes in the background brightness. Based on the findings of this study, degradation in image quality can be improved, which may occur when the size of the input image is changed at a later time, and also, contributions can be made when it comes to the reproduction of effective sold three-dimensional structures that reflect visual qualities when processing 3D holographic imagery, in addition to 2D imagery.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.46 no.3
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• pp.44-51
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• 2009

It is very important to verify generated setup errors in cancer therapy by using a high energy radiation and to perform the precise radiation therapy. Specially, the verification of treatment position is very crucial in special therapies like fractionated stereotatic radiotherapy (FSRT). The FSRT uses normally high-dose, small field size for treating small intracranial lesions. To estimate the developed FSRT system, the isocenter accuracy of gantry, couch and collimator were performed and a total of inaccuracy was less than ${\pm}1mm$. Precise beam targeting is crucial when using high-dose, small field size FSRT for treating small intracranial lesions. The EPID image of the 3mm lead ball mounted on the isocenter with a 25mm collimator cone was acquired and detected to the extent of one pixel (0.76mm) after comparing the difference between the center of a 25mm collimator cone and a 3 mm ball after processing the EPID image. In this paper, the radiation treatment efficiency can be improved by performing precise radiation therapy with a developed video based EPID and FSRT at near real time

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.34 no.1
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• pp.53-62
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• 2016

In recent years, UAV Photogrammetry based on an ultra-light UAS(Unmanned Aerial System) installed with a low-cost compact navigation device and a camera has attracted great attention through fast and accurate acquirement of geo-spatial data. In particular, UAV Photogrammetry do gradually replace the traditional aerial photogrammetry because it is able to produce DEMs(Digital Elevation Models) and Orthophotos rapidly owing to large amounts of high resolution image collection by a low-cost camera and image processing software combined with computer vision technique. With these advantages, UAV-Photogrammetry has therefore been applying to a large scale mapping and cadastral surveying that require accurate position information. This paper presents experimental results of an accuracy performance test with images of 4cm GSD from a fixed wing UAS to demarcate parcel boundaries in agricultural area. Consequently, the accuracy of boundary point extracted from UAS orthoimage has shown less than 8cm compared with that of terrestrial cadastral surveying. This means that UAV images satisfy the tolerance limit of distance error in cadastral surveying for the scale of 1: 500. And also, the area deviation is negligible small, about 0.2%(3.3m²), against true area of 1,969m² by cadastral surveying. UAV-Photogrammetry is therefore as a promising technology to demarcate parcel boundaries.

• Journal of Internet of Things and Convergence
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• v.10 no.2
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• pp.69-75
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• 2024

This paper proposes an IoT-based indoor autonomous driving system that applies SLAM (Simultaneous Localization And Mapping) and Navigation techniques in a ROS (Robot Operating System) environment based on TurtleBot3. The proposed autonomous driving system can be applied to indoor autonomous wheelchairs and robots. In this study, the operation was verified by applying it to an indoor self-driving wheelchair. The proposed autonomous driving system provides two functions. First, indoor environment information is collected and stored, which allows the wheelchair to recognize obstacles. By performing navigation using the map created through this, the rider can move to the desired location through autonomous driving of the wheelchair. Second, it provides the ability to track and move a specific logo through image recognition using OpenCV. Through this, information services can be received from guides wearing uniforms with the organization's unique logo. The proposed system is expected to provide convenience to passengers by improving mobility, safety, and usability over existing wheelchairs.