• Journal of the Ergonomics Society of Korea
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• v.36 no.5
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• pp.395-409
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• 2017

Objective: The purpose of this study was to optimize the number and positions of foot pressure sensors using the reliability analysis of the center of pressure (COP) in smart shoes. Background: Foot pressure can be different according to foot region, and it is important which region of the foot pressure needs to be measured. Method: Thirty adults (age: $20.5{\pm}1.8years$, body weight: $71.4{\pm}6.5kg$, height: $1.76{\pm}0.04m$) participated in this study. The foot pressure data were collected using the insole of Pedar-X system (Novel GmbH, USA) with a sampling frequency of 100Hz during 1.3m/s speed walking on the treadmill (Instrumented treadmill, Bertec, USA). The intraclass correlation coefficients (ICC) were calculated between the COP positions using 4, 5, 6, 7, 8, and 99 sensors, while one-way repeated measure ANOVA was performed between the standard deviation (SD) of the COP positions. Results: The medio-lateral (M/L) COP position using 99 sensors was positively correlated with the M/L COP positions using 6, 7, and 8 sensors; however, it was not correlated with the M/L COP positions using 4 and 5 sensors during landing phase (1~4%) (p<.05). The antero-posterior (A/P) COP position using 99 sensors was positively correlated with the A/P COP positions using 4, 5, 6, 7, and 8 sensors (p<.05). The SD of the COP position using 99 sensors was smaller than the SD of the M/L COP positions using 4, 5, 6, 7, and 8 sensors (p<.05). Conclusion: Based on our findings, it is desirable to arrange at least 6 sensors in smart shoes. Application: The study of optimizing the number and positions of foot pressure sensors would contribute to developing more effective smart shoes using foot pressure technology.

• Journal of Korea Society of Industrial Information Systems
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• v.25 no.3
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• pp.53-59
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• 2020

This paper proposes color segmentation for detecting missing persons in a smart lighting system using radar and camera sensors. Recently, smart lighting systems built-in radar and cameras have been efficient in saving energy and searching for missing persons, simultaneously. In smart lighting systems, radar detects moving objects and then the lights turn on and camera records. The video recorded is useful to find out missing persons. The color of their clothes worn in missing persons is one of critical hints to look for missing persons. Therefore, color segmentation is an effective means for detecting the color of their clothes. In this paper, during the color segmentation step, the ROI(Region of interest) setting based on the size of an object is applied and the background is reduced. According to experimental results, the color segmentation has good accuracy of more than 97%.

• Smart Media Journal
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• v.6 no.4
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• pp.32-40
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• 2017

In this paper, a robust text detection method based on edge enhanced contrasting extremal region (CER) is proposed using stroke width transform (SWT) and tensor voting. First, the edge enhanced CER extracts a number of covariant regions, which is a stable connected component from input images. Next, SWT is created by the distance map, which is used to eliminate non-text regions. Then, these candidate text regions are verified based on tensor voting, which uses the input center point in the previous step to compute curve salience values. Finally, the connected component grouping is applied to a cluster closed to characters. The proposed method is evaluated with the ICDAR2003 and ICDAR2013 text detection competition datasets and the experiment results show high accuracy compared to previous methods.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.7
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• pp.3333-3350
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• 2019

The smart jammer launches jamming attacks which degrade the transmission reliability. In this paper, smart jamming attacks based on the communication probability over different channels is considered, and an anti-jamming Q learning algorithm (AQLA) is developed to obtain anti-jamming knowledge for the local region. To accelerate the learning process across multiple regions, a multi-regional intelligent anti-jamming learning algorithm (MIALA) which utilizes transferred knowledge from neighboring regions is proposed. The MIALA algorithm is evaluated through simulations, and the results show that the it is capable of learning the jamming rules and effectively speed up the learning rate of the whole communication region when the jamming rules are similar in the neighboring regions.

• Journal of Korea Multimedia Society
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• v.19 no.2
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• pp.418-427
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• 2016

A smart parking management requires to track a vehicle in a indoor parking lot and to detect the place where the vehicle is parked. An advanced parking system watches all space of the parking lot with CCTV cameras. We can use these cameras for vehicles tracking and detection. In order to cover a wide area with a camera, a fisheye lens is used. In this case the shape and size of an moving vehicle vary much with distance and angle to the camera. This makes vehicle detection and tracking difficult. In addition to the fisheye lens, the vehicle headlights also makes vehicle detection and tracking difficult. This paper describes a method of realtime vehicle detection and tracking robust to the harsh situation described above. In each image frame, we update the region of a vehicle and estimate the vehicle movement. First we approximate the shape of a car with a quadrangle and estimate the four sides of the car using multiple histograms of oriented gradient. Second we create a template by applying a distance transform to the car region and estimate the motion of the car with a template matching method.

• Journal of Computing Science and Engineering
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• v.5 no.3
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• pp.161-166
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• 2011

We present a fast algorithm for Korean text extraction and segmentation from subway signboards using smart phone sensors in order to minimize computational time and memory usage. The algorithm can be used as preprocessing steps for optical character recognition (OCR): binarization, text location, and segmentation. An image of a signboard captured by smart phone camera while holding smart phone by an arbitrary angle is rotated by the detected angle, as if the image was taken by holding a smart phone horizontally. Binarization is only performed once on the subset of connected components instead of the whole image area, resulting in a large reduction in computational time. Text location is guided by user's marker-line placed over the region of interest in binarized image via smart phone touch screen. Then, text segmentation utilizes the data of connected components received in the binarization step, and cuts the string into individual images for designated characters. The resulting data could be used as OCR input, hence solving the most difficult part of OCR on text area included in natural scene images. The experimental results showed that the binarization algorithm of our method is 3.5 and 3.7 times faster than Niblack and Sauvola adaptive-thresholding algorithms, respectively. In addition, our method achieved better quality than other methods.

• Journal of Fashion Business
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• v.23 no.1
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• pp.1-13
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• 2019

This study aimed to analyze the preference, the factors of benefits sought, and the difference of benefits sought for smart clothing based on demographic characteristics. This survey study used questionnaire. The subjects of the survey consisted of men and women with ages ranging from twenty to fifty years old, who were living in Gyeongnam region. For the collected data analysis, Factor analysis, t-test, ANOVA, and Duncan multiple range tests were used by SPSS 23. The results obtained were as follows. The different analysis results for smart clothing based on demographic characteristics showed a significant difference with respect to marital status, age, monthly income, and occupation, but showed an insignificant difference with respect to gender. The factors of benefits sought for smart clothing were extracted from five factors-pursuit; image innovation and improvement, pursuit of healthcare, pursuit of body protection, pursuit of amusement and pleasure, and pursuit of hi-tech function. The different analysis results of smart clothing according to demographic characteristics showed a significant difference for pursuit of healthcare only with respect to gender, for pursuit of image innovation and improvement, healthcare, amusement and pleasure, and hi-tech function with respect to marital status, for pursuit of image innovation and improvement, healthcare, amusement and pleasure, and hi-tech function with respect to age, for pursuit of healthcare and body protection with respect to monthly income, and for all five factors with respect to occupation.

• Proceedings of the Korea Information Processing Society Conference
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• 2010.11a
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• pp.1388-1391
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• 2010

In this paper, we present a design and implementation of U-learning system using pen based augmented reality approach. Student has been given a smart pen and a smart study book, which is similar to the printed material already serviced. However, we print the study book using CMY inks, and embed perceptually invisible dot patterns using K ink. Smart pen includes (1) IR LED for illumination, IR pass filter for extracting the dot patterns, and (3) camera for image captures. From the image sequences, we perform topology analysis which determines the topological distance between dot pixels, and perform error correction decoding using four position symbols and five CRC symbols. When a student touches a smart study books with our smart pen, we show him/her multimedia (visual/audio) information which is exactly related with the selected region. Our scheme can embed 16 bit information, which is more than 200% larger than previous scheme, which supports 7 bits or 8 bits information.

• The Journal of the Korea Contents Association
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• v.12 no.12
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• pp.524-532
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• 2012

According to increasing in number of smart phone subscribers to offer the convenience of users, wide range of applications in various fields have emerged. Recently, a lot of applications are being developed to provide a way of receiving information according to the user's current location. Also, the news seems difficult to provide the necessary information among the numerous data. Especially, it is difficult to find the news that associated with the region. There are many applications that provide news, but there is no system to provide news information according to the user's location information in domestic, so users not receive the news of the region. In this paper, we propose a news retrieval application which provides users with news around by using the location information of smart phone users. Because this system provides news of the region, it has the advantage to obtain the around information easily. The proposed system, whose name is 'ChungbukN', provides news that receives data at chungbuk comprehensive daily newspaper 'Daily Chungbuk'.

• IEIE Transactions on Smart Processing and Computing
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• v.4 no.2
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• pp.110-114
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• 2015

This paper reports a novel object-detection technique in video sequences. The proposed algorithm consists of detection of objects in illuminated and occluded videos by using object features and a neural network technique. It consists of two functional modules: region-based object feature extraction and continuous detection of objects in video sequences with region features. This scheme is proposed as an enhancement of the Lowe's scale-invariant feature transform (SIFT) object detection method. This technique solved the high computation time problem of feature generation in the SIFT method. The improvement is achieved by region-based feature classification in the objects to be detected; optimal neural network-based feature reduction is presented in order to reduce the object region feature dataset with winner pixel estimation between the video frames of the video sequence. Simulation results show that the proposed scheme achieves better overall performance than other object detection techniques, and region-based feature detection is faster in comparison to other recent techniques.