• KSII Transactions on Internet and Information Systems (TIIS)
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• 제3권1호
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• pp.84-95
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• 2009

The ubiquitous smart home is the home of the future, which exploits context information from both the human and the home environment, providing an automatic home service for the human. Human location and motion are the most important contexts in the ubiquitous smart home. In this paper, we present a real-time human tracker that predicts human location and motion for the ubiquitous smart home. The system uses four network cameras for real-time human tracking. This paper explains the architecture of the real-time human tracker, and proposes an algorithm for predicting human location and motion. To detect human location, three kinds of images are used: $IMAGE_1$ - empty room image, $IMAGE_2$ - image of furniture and home appliances, $IMAGE_3$ - image of $IMAGE_2$ and the human. The real-time human tracker decides which specific furniture or home appliance the human is associated with, via analysis of three images, and predicts human motion using a support vector machine (SVM). The performance experiment of the human's location, which uses three images, lasted an average of 0.037 seconds. The SVM feature of human motion recognition is decided from the pixel number by the array line of the moving object. We evaluated each motion 1,000 times. The average accuracy of all types of motion was 86.5%.

• The Journal of Korean Institute of Communications and Information Sciences
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• 제19권11호
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• pp.2094-2105
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• 1994

This paper contains a Hough transform based projection method derived from Radon transform for tracking dim unresolved(sub-pixel) moving targets that move along straight line parths across a time sequential image data. In contrast to several recently presented Hough transform methods using a compressed image referred to as the track map our proposed technique utilizing a set of projections taken along arbitrary orientations effectively increases the changes of target detection, and creates a robust track estimation environment by incorporating all the available knowledge obtained from the projections. Moreover, in order to quantitatively assess the estimation capability of the projection-based Hough transform algorithm, the analytical bounds on the Hough space parameter errors introduced by image space noise contamination are derived. The simulation yielded promising results of estimating the track parameters even under low signal to noise rations when our technique was tested against the time sequential sets of real infrared image data referred to as the HiCamps.

• Journal of Computational Design and Engineering
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• 제1권3호
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• pp.202-212
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• 2014

To survive in the current shipbuilding industry, it is of vital importance for shipyards to have the ship components' accuracy evaluated efficiently during most of the manufacturing steps. Evaluating components' accuracy by comparing each component's point cloud data scanned by laser scanners and the ship's design data formatted in CAD cannot be processed efficiently when (1) extract components from point cloud data include irregular obstacles endogenously, or when (2) registration of the two data sets have no clear direction setting. This paper presents reformative point cloud data processing methods to solve these problems. K-d tree construction of the point cloud data fastens a neighbor searching of each point. Region growing method performed on the neighbor points of the seed point extracts the continuous part of the component, while curved surface fitting and B-spline curved line fitting at the edge of the continuous part recognize the neighbor domains of the same component divided by obstacles' shadows. The ICP (Iterative Closest Point) algorithm conducts a registration of the two sets of data after the proper registration's direction is decided by principal component analysis. By experiments conducted at the shipyard, 200 curved shell plates are extracted from the scanned point cloud data, and registrations are conducted between them and the designed CAD data using the proposed methods for an accuracy evaluation. Results show that the methods proposed in this paper support the accuracy evaluation targeted point cloud data processing efficiently in practice.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• 제11권2호
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• pp.219-224
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• 2011

Recently increasing importance of information security, personal security is researched. Among them, biometrics research is very good at recognition and security particularly in terms of iris recognition. Recent hospital physicians and employees for access control is emphasized. But most of them, easy-employee card access control systems are used. It has difficulties of iris recognition on the issue of accurate iris recognition algorithm to eliminate noise and inaccuracy of pretreatment methods for recognition from existing research. Therefore, this paper complements existing encryption methods to the disadvantages of biometric iris recognition using high-access records in the hospital management system is applied. In addition to conventional pretreatment process to increase recognition eyebrows when mask line component added to the extraction mask, the correct preparation method, and accordingly proposed to improve the recognition of records management systems offer access to the hospital.

• Journal of the Korea Convergence Society
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• 제6권1호
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• pp.7-16
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• 2015

A segmentation process extracts an interesting area of barcode in an image and gives a crucial impart on the performance of barcode verifier. Previous segmentation methods occurs some issues as follows. First, it is very hard to determine a threshold of length in Hough Line transform because it is sensitive. Second, Morphology transform delays the process when you conduct dilation and erosion operations during the image extraction. Therefore, we proposes a novel Converged Harris Corner detection-based segmentation method to detect an interesting area of barcode in Data Matrix. In order to evaluate the performance of proposed method, we conduct experiments by a dataset of barcode in accordance with size and location in an image. In result, our method solves the problems of delay and surrounding environments, threshold setting, and extracts the barcode area 100% from test images.

• Journal of the Korean Institute of Telematics and Electronics B
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• 제31B권11호
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• pp.36-44
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• 1994

In this paper, a high-level process control language is developed to construct multi-loop controllers for large scale process control systems. Function locks are defined which are basic functions necessary to configure a multi-loop controller. Each block is presented to the function code which is a line of ASCII codes and has the characteristics to be simple and to be easily understood. A control algorithm for a process is attained by means of the arrangement of function codes with order. In order to be used to various environments of target hardwares, a transformation program is prepared that transfers a control program configured by function codes to a C-language program. The proposed control language is easy and simple to use, possible to expend, and able to apply to various control systems. Simulation results are included to show the availability for the usage of the proposed control language in real world.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• 제26권3호
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• pp.311-316
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• 2015

This paper presents a design method for thin but wideband absorbers using resistive sheets. Its equivalent circuit consists of a series RLC resonant circuit and a short-terminated transmission line. Based on this equivalent circuit, we presented the three conditions for an electromagnetic absorber which has a thickness less than a quarter wavelength and wide absorption bandwidth at center frequency. By using an root-finding algorithm, the equivalent resistance, capacitance, and inductance of the absorbers are obtained. These equivalent circuit values for the absorber surface can be realized by a 2D periodic cross-shaped structure which has required surface resistance. Using the design method, we have designed the absorber which has 18.75 mm($67.5^{\circ}$ electrical length) thickness and 90 % absorption bandwidth of 116 % bandwidth at 3 GHz.

• Journal of Korean Society of Coastal and Ocean Engineers
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• 제20권4호
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• pp.333-341
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• 2008

A remote sensing technique to identify trajectories of breaking waves in the surf zone using oblique digital nearshore videos is proposed. The noise arising from white foam induced by wave breaking has hindered accurate remote sensing of wave properties in the surf zone. For this reason, this paper focuses on image processing to remove the noise and wave trajectory identification essential for wave property estimation. The nearshore video imagery sampled at 3 Hz are used, covering length scale(100 m). Original image sequences are processed through image frame differencing and directional low-pass image filtering to remove the noise characterized by high frequencies in the video imagery. The extraction of individual wave crest features is conducted using a Radon transform-based line detection algorithm in the processed cross-shore image timestacks having a two-dimensional space-time domain. The number of valid wave crest trajectories identified corresponds to about 2/3 of waves recorded by the in-situ sensors.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제4권3호
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• pp.243-257
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• 2010

Rapid developments in wireless sensor networks have extended many applications, hence, many studies have developed wireless sensor network positioning systems for indoor environments. Among those systems, the Global Position System (GPS) is unsuitable for indoor environments due to Line-Of-Sight (LOS) limitations, while the wireless sensor network is more suitable, given its advantages of low cost, easy installation, and low energy consumption. Due to the complex settings of indoor environments and the high demands for precision, the implementation of an indoor positioning system is difficult to construct. This study adopts a low-cost positioning method that does not require additional hardware, and uses the received signal strength (RSS) values from the receiver node to estimate the distance between the test objects. Since many objects in indoor environments would attenuate the radio signals and cause errors in estimation distances, knowing the path loss exponent (PLE) in an environment is crucial. However, most studies preset a fixed PLE, and then substitute it into a radio propagation loss model to estimate the distance between the test points; such method would lead to serious errors. To address this problem, this study proposes a Path Loss Exponent Estimation Algorithm, which uses only four beacon nodes to construct a radio propagation loss model for an indoor environment, and is able to provide enhanced positioning precision, accurate positioning services, low cost, and high efficiency.

• Journal of the Korean Society for Nondestructive Testing
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• 제35권1호
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• pp.1-11
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• 2015

In this study, an online seed potato sorting system using a visible and near infrared (40 1100 nm) transmittance spectral technique and statistical model was evaluated for the nondestructive determination of infected and sound seed potatoes. Seed potatoes that had been artificially infected with Pectobacterium atrosepticum, which is known to cause a soil borne disease infection, were prepared for the experiments. After acquiring transmittance spectra from sound and infected seed potatoes, a determination algorithm for detecting infected seed potatoes was developed using the partial least square discriminant analysis method. The coefficient of determination($R^2_p$) of the prediction model was 0.943, and the classification accuracy was above 99% (n = 80) for discriminating diseased seed potatoes from sound ones. This online sorting system has good potential for developing a technique to detect agricultural products that are infected and contaminated by pathogens.