• ETRI Journal
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• v.27 no.3
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• pp.294-303
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• 2005

In this paper, a supervised algorithm for the evaluation of geophysical sites using a multi-level cellular neural network (ML-CNN) is introduced, developed, and applied to real data. ML-CNN is a stochastic image processing technique based on template optimization using neighborhood relationships of the pixels. The separation/enhancement and border detection performance of the proposed method is evaluated by various interesting real applications. A genetic algorithm is used in the optimization of CNN templates. The first application is concerned with the separation of potential field data of the Dumluca chromite region, which is one of the rich reserves of Turkey; in this context, the classical approach to the gravity anomaly separation method is one of the main problems in geophysics. The other application is the border detection of archeological ruins of the Hittite Empire in Turkey. The Hittite civilization sites located at the Sivas-Altinyayla region of Turkey are among the most important archeological sites in history, one reason among others being that written documentation was first produced by this civilization.

• Journal of Electrical Engineering and Technology
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• v.12 no.1
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• pp.363-372
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• 2017

This paper presents a novel face recognition algorithm based on the deep convolution neural network and key point detection jointed local binary pattern methodology to enhance the accuracy of face recognition. We firstly propose the modified face key feature point location detection method to enhance the traditional localization algorithm to better pre-process the original face images. We put forward the grey information and the color information with combination of a composite model of local information. Then, we optimize the multi-layer network structure deep learning algorithm using the Fisher criterion as reference to adjust the network structure more accurately. Furthermore, we modify the local binary pattern texture description operator and combine it with the neural network to overcome drawbacks that deep neural network could not learn to face image and the local characteristics. Simulation results demonstrate that the proposed algorithm obtains stronger robustness and feasibility compared with the other state-of-the-art algorithms. The proposed algorithm also provides the novel paradigm for the application of deep learning in the field of face recognition which sets the milestone for further research.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.45 no.6
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• pp.42-47
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• 2008

In this article a novel constant amplitude precoding for impulse UWB system is proposed. According to IEEE 802.15.4a, impulse UWB can be used in indoor localization and sensor data transmission. Most USN(ubiquitous sensor networks) needs multiple access. However impulse UWB system has a limited capability to detect superpositioned signal induced by multiple access. To overcome this problem we have adopted the concept of CAMC(Constant Amplitude Multi-Code) deviced by Wada and Kim. The proposed system consists of systematic constant amplitude precoding and LDPC decoding. And this system shows a good BER performance in computer simulation.

• Proceedings of the KIEE Conference
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• 2011.07a
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• pp.1590-1591
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• 2011

In this paper, the UV corona camera was developed using the solar blind and Multi Channel Plate(MCP) technology for the target localization of UV camera. UV camera developed a $6.4^{\circ}{\times}4.8^{\circ}$ of the field of view as a conventional camera to diagnose a wide range of slightly enlarged, and power equipment to measure the distance between the camera and the distance meter has been attached. The UV camera was developed and measured using a UV image, as applied voltage increased ultraviolet images of the phenomenon could be obtained. And we investigated properties of UV corona image on insulator in salt water environments. From the results, the breakdown voltage was decreased and UV images were taken at low voltages and the UV image is rapidly increased with increasing High voltage.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.23 no.4
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• pp.617-627
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• 2013

Wireless communication technology such as NFC and RFID makes the data transfer between devices much easier. Instead of the irksome typing of passwords, users are able to simply authenticate themselves with their smart cards or smartphones. Relay attack, however, threatens the security of token-based, something-you-have authentication recently. It efficiently attacks the authentication system even if the system has secure channels, and moreover it is easy to deploy. Distance bounding or localization of two devices has been proposed to detect relay attacks. We describe the disadvantages and weakness of existing methods and propose a new way to detect relay attacks by recording a background noise.

• Journal of Information Processing Systems
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• v.13 no.2
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• pp.385-399
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• 2017

Nowadays, with the development of signal processing technique, the protection to the integrity and authenticity of images has become a topic of great concern. A blind image authentication technology with high tamper detection accuracy for different common attacks is urgently needed. In this paper, an improved fragile watermarking method based on local binary pattern (LBP) is presented for blind tamper location in images. In this method, a binary watermark is generated by LBP operator which is often utilized in face identification and texture analysis. In order to guarantee the safety of the proposed algorithm, Arnold transform and logistic map are used to scramble the authentication watermark. Then, the least significant bits (LSBs) of original pixels are substituted by the encrypted watermark. Since the authentication data is constructed from the image itself, no original image is needed in tamper detection. The LBP map of watermarked image is compared to the extracted authentication data to determine whether it is tampered or not. In comparison with other state-of-the-art schemes, various experiments prove that the proposed algorithm achieves better performance in forgery detection and location for baleful attacks.

• Journal of Advanced Marine Engineering and Technology
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• v.24 no.2
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• pp.82-89
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• 2000

Edge detection is the first step and very important step in image analysis. In this paper, proposed edge detection operators based on informations of edge types and it is different from other classical edge detection operators such as gradient and surface fitting operators. The first, we defined characteristics of edge types such as localization, thinness, length. The second, we defined valid edge types and ideal edge pixel positions in $3\times3$window based on edge characteristics of edge types. And we proposed edge detection algorithm and twelve windows based on valid edge types. In specially, proposed algorithm was shown better performence of edge detection than other operators such as gradient operator and the LoG(Laplacian of Gaussian) operator of zero crossings.

• The Journal of Korea Robotics Society
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• v.2 no.4
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• pp.317-326
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• 2007

Recently, robotic automation in clinical laboratory becomes of keen interest as a fusion of bio and robotic technology. In this paper, we present a new robotic platform for clinical tests suitable for small or medium sized laboratories using mobile robots. The mobile robot called Mobile Agent is designed as transfer system of blood samples, reagents, microplates, and any instruments. Also, the developed mobile agent can perform diverse tests simultaneously based on its cooperative and distributed ability. The driving circuits for the mobile agent are embedded in the robot, and each mobile agent communicates with other agents by using Bluetooth communication. The RFID system is used to recognize patient information. Also, the magnetic hall sensor is embedded to remove and compensate the cumulated error of locomotion at the bottom of mobile agent. The proposed mobile agent can be easily used for various applications because it is designed to be compatible with general software development tools. The Mobile agents are manufactured, and feasibility of the robot and localization of the agents using magnetic hall sensor are validated by preliminary experiments.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.11
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• pp.5527-5545
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• 2019

Through-wall ultra-wide band (UWB) radar has been considered as one of the preferred and non-contact technologies for the targets detection owing to the better time resolution and stronger penetration. The high time resolution is a result of a larger of bandwidth of the employed UWB pulses from the radar system, which is a useful tool to separate multiple targets in complex environment. The article emphasised on human subject localization and detection. Human subject usually can be detected via extracting the weak respiratory signals of human subjects remotely. Meanwhile, the range between the detection object and radar is also acquired from the 2D range-frequency matrix. However, it is a challenging task to extract human respiratory signals owing to the low signal to clutter ratio. To improve the feasibility of human respiratory signals detection, a new method is developed via analysing the standard deviation based kurtosis of the collected pulses, which are modulated by human respiratory movements in slow time. The range between radar and the detection target is estimated using joint time-frequency analysis (JTFA) of the analysed characteristics, which provides a novel preliminary signature for life detection. The breathing rates are obtained using the proposed accumulation method in time and frequency domain, respectively. The proposed method is validated and proved numerically and experimentally.

• Current Research on Agriculture and Life Sciences
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• v.30 no.1
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• pp.1-11
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• 2012

We identified cdf based on screening of the Arabidopsis cDNA library for functional suppressors of the AtBI-1 (a gene described to suppress the cell death induced by Bax gene expression in yeast). The cdf was located on Chr. V and was composed of 5 exons and 4 introns. It encodes a protein of 258 amino acid residues with a molecular weight of 28.8 kDa. The protein has 3 transmembrane domains in the C-terminal region. The cdf has one homologue, named cdf2, which was found in Arabidopsis. Like cdf, cdf2 also induced growth defect in yeast. The effect of the cell growth defect factor was somewhat lower than Bax. cdf could arrest the growth of yeast. Its localization to the nucleus was essential for the suppression of yeast cell proliferation. Morphological abnormality of intracellular network, which is a hallmark of AtBI-1, was attenuated by expression of cdf.