• Journal of Integrative Natural Science
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• v.11 no.4
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• pp.167-183
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• 2018

Electroencephalogram (EEG) recording provides a new way to support human-machine communication. It gives us an opportunity to analyze the neuro-dynamics of human cognition. Machine learning is a powerful for the EEG classification. In addition, machine learning can compensate for high variability of EEG when analyzing data in real time. However, the optimal EEG electrode location must be prioritized in order to extract the most relevant features from brain wave data. In this paper, we propose an intelligent system model for the extraction of EEG data by training the optimal electrode location of EEG in a specific problem. The proposed system is basically a fuzzy system and uses a neural network structurally. The fuzzy clustering method is used to determine the optimal number of fuzzy rules using the features extracted from the EEG data. The parameters and weight values found in the process of determining the number of rules determined here must be tuned for optimization in the learning process. Genetic algorithms are used to obtain optimized parameters. We present useful results by using optimal rule numbers and non - symmetric membership function using EEG data for four movements with the right arm through various experiments.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.51 no.3
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• pp.108-111
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• 2002

This paper proposes an new water mark embedding and extraction technique which extends the direct sequence spread spectrum technique. The proposed technique approximates the complexity of image and block in spatial domain using Laplacian filtering and watermark is adaptively embedded in the mid-frequency DCT components. Local parity bits are attached to higher-frequency DCT components and they are used to detect extraction errors and correct those errors. In extraction process the proposed method boosts the higher frequency components of image and extracts the watermark by demodulation and this information is verified and adjusted by parity bits. Experimental results show it is invisible and robust to several external attacks.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.97-100
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• 1996

In this paper, we describe an algorithm which estimate road following direction using the vanishing point property and obstacle detection. This method of detecting the lane markers in a set of continuous lane highway images using linear approximation is presented. This algorithm is designed for accurate and robust extraction of this data as well as high processing speed. Also, this algorithm reckon distance and chase about an obstacle. It include four algorithms which are lane prediction, lane extraction, road following parameter estimation and obstacle detection algorithm. High accuracy was proven by quantitative evaluation using simulated images. Both robustness and the practicality of real time video rate processing were then confirmed through experiment using VTR real road images.

• The Journal of Information Technology
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• v.12 no.4
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• pp.25-32
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• 2009

Iris recognition is a biometric technology which can identify a person using the iris pattern. It is important for the iris recognition system to extract the feature which is invariant to changes in iris patterns. Those changes can be occurred by the influence of lights, changes in the size of the pupil, and head tilting. This paper is appropriate for the embedded environment using local gradient histogram embedded system using iris feature extraction methods have implement. The proposed method enables high-speed feature extraction and feature comparison because it requires no additional processing to obtain the rotation invariance, and shows comparable performance to the well-known previous methods.

• 제어로봇시스템학회:학술대회논문집
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• 1991.10a
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• pp.669-675
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• 1991

Based on process analysis as well as extensive operation experience, two fuzzy expert control algorithms, for startup and control, are proposed for a supercritical fluid extraction process which has high interacting multivariable structure. In the proposed algorithms, a new simple defuzzification method which only requires four fundamental arithmetic rules is also presented. Through numerical simulations, control performance using the proposed control algorithm is compared with that of a different fuzzy algorithm by an other researcher and that of conventional PID-type controllers which are tuned by well-known optimal criteria. Also, the proposed control algorithm has been tested to the bench scale supercritical fluid extraction process. As a consequence, the proposed fuzzy expert controller has shown fast and robust control performance while the other controllers show sluggish and/or highly oscillatory responses.

• Proceedings of the IEEK Conference
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• 1999.11a
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• pp.581-584
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• 1999

In order to retrieve the rotated image within database by the content based image retrieval system, the algorithms with rotation robustness is usually applied in the procedure of the feature extraction. In that case, it requires much calculation time for feature extraction and much indexed data for feature indexing. Thus. in this paper. we propose the rotation robust algorithm using the block variance of the projected vector. The algorithm does not require additional calculation for feature extraction and is executed within query time by comparing the extracted data. Proposed method can be processed through database including various size of images with shape information and executed with fast response time in implementation.

• Proceedings of the IEEK Conference
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• 2007.07a
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• pp.313-314
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• 2007

In this paper, we suggest robust object extraction algorithm taking advantage of efficient Belief Propagation method. It does not get a disparity information because of uniform region and occlusion region etc. on initial depth map that use forward direction disparity information although is object area. Therefore, We run parallel backward disparity information and brightness information for certain object extraction.

• Mass Spectrometry Letters
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• v.12 no.4
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• pp.186-191
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• 2021

A new method for chemical separation of light rare-earth elements (LREEs) using gas-pressurized extraction chromatography (GPEC) is described. GPEC is a microscale column chromatography system that features a constant flow of solvents, which is created by pressurized nitrogen gas. The separation column with a Teflon tubing was packed with LN resin. The proposed GPEC method facilitates production of lesser chemical wastes and faster separation owing to the use of low solvent volume compared to traditional column chromatography. We evaluated the separation of Ba, La, Ce, and Nd using various elution solvents. The column reproducibility of the proposed GPEC system ranged from 2.4% to 4.9% with RSDs of recoveries, and the column-to-column reproducibility ranged from 3.1% to 6.3% with RSDs of recoveries. The proposed technique is robust, and it can be useful for the fast separation of LREEs.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.40 no.2
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• pp.79-89
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• 2022

Images taken using drones have been applied to fields that require rapid decision-making as they can quickly construct high-quality 3D spatial information for small regions. To construct spatial information based on drone images, it is necessary to determine the relationship between images by extracting keypoints between adjacent drone images and performing image matching. Therefore, in this study, three study regions photographed using a drone were selected: a region where parking lots and a lake coexisted, a downtown region with buildings, and a field region of natural terrain, and the performance of AKAZE (Accelerated-KAZE), BRISK (Binary Robust Invariant Scalable Keypoints), KAZE, ORB (Oriented FAST and Rotated BRIEF), SIFT (Scale Invariant Feature Transform), and SURF (Speeded Up Robust Features) algorithms were analyzed. The performance of the keypoints extraction algorithms was compared with the distribution of extracted keypoints, distribution of matched points, processing time, and matching accuracy. In the region where the parking lot and lake coexist, the processing speed of the BRISK algorithm was fast, and the SURF algorithm showed excellent performance in the distribution of keypoints and matched points and matching accuracy. In the downtown region with buildings, the processing speed of the AKAZE algorithm was fast and the SURF algorithm showed excellent performance in the distribution of keypoints and matched points and matching accuracy. In the field region of natural terrain, the keypoints and matched points of the SURF algorithm were evenly distributed throughout the image taken by drone, but the AKAZE algorithm showed the highest matching accuracy and processing speed.

• Journal of Broadcast Engineering
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• v.9 no.1
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• pp.64-73
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• 2004

A robust watermarking algorithm is proposed for 3D mesh models. Watermark is inserted into the 2D image which is extracted from the target 3D model. Each Pixel value of the extracted 2D image represents a distance from the predefined reference points to the face of the given 3D model. This extracted image is defined as “range image” in this paper. Watermark is embedded into the range image. Then, watermarked 3D mesh is obtained by modifying vertices using the watermarked range Image. In extraction procedure, the original model is needed. After registration between the original and the watermarked models, two range images are extracted from each 3D model. From these images. embedded watermark is extracted. Experimental results show that the proposed algorithm is robust against the attacks such as rotation, translation, uniform scaling, mesh simplification, AWGN and quantization of vertex coordinates.