• The Journal of the Korea Contents Association
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• v.4 no.4
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• pp.205-213
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• 2004

In this paper, we proposed a wavelet phase-only filter modulation synthetic discriminant function joint transform correlator(WPOfSDF-JTC) for scale invariant pattern recognition, and an improved algorithm to reduce the filter synthesis time. Computer simulation showed that the proposed filter has better SNR than CWMF if input image has random noise and the improved synthesis algorithm can reduce the iteration time. We used frequency selective JTC to solve the problem of the optical alignment and eliminate the autocorrelation and crosscorrelation between each input image.

• Bulletin of the Korean Chemical Society
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• v.35 no.1
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• pp.123-128
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• 2014

In this study, we have investigated the flow rate effects of Ag nanoparticle (NP) suspensions on the progress of the cell cycle by using a microfluidic image cytometry (${\mu}FIC$)-based approach. Compared with the conventional "static" exposure conditions, enhancements in G2 phase arrest were observed for the cells under continuously flowing "dynamic" exposure conditions. The "dynamic" exposure conditions, which mimic in vivo systems, induced an enhanced cytotoxicity by accelerating G2 phase arrest and subsequent apoptosis processes. Moreover, we have also shown that the increases in delivered NP dose due to the continuous supply of Ag NPs contributed dominantly to the enhanced cytotoxicity observed under the "dynamic" exposure conditions, while the shear stress caused by these slowly flowing fluids (i.e., flow rates of 6 and $30{\mu}L/h$) had only a minor influence on the observed enhancement in cytotoxicity.

• Journal of Electrical Engineering and information Science
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• v.2 no.5
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• pp.79-88
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• 1997

This paper introduces a new energy function, as maximum a posteriori(MAP) estimate of binocular disparity, that can deal with both random dot stereo-gram(RDS) and natural scenes. The energy function uses phase-magnitude as features to detect only the shift for a pair of corrupted conjugate images. Also we adopted Fleet singularity that effectively detects unstable areas of image plant and thus eliminates in advance error-prone stereo mathcing. The multi-scale concept is applied to the multi laser architecture that can search the solutions systematically from coarse to fine details and thereby avoids drastically the local minima. Using mean field approximation, we obtained a compact representation that is suitable for fast computation. In this manner, the energy function satisfies major natural constraints and requirements for implementing parallel relaxation. As an experiment, the proposed algorithm is applied to RDS and natural stereo images. As a result we will see that it reveals good performance in terms of recognition errors, parallel implementation, and noise characteristics.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.45 no.4
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• pp.10-21
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• 2008

The present paper propose a real-time moving object recognition and tracking method using the wavelet-based neural network and invariant moments. Candidate moving region detection phase which is the first step of the proposed method detects the candidate regions where a pixel value changes occur due to object movement based on the difference image analysis between continued two image frames. The object recognition phase which is second step of proposed method recognizes the vehicle regions from the detected candidate regions using wavelet neurual-network. From object tracking Phase which is third step the recognized vehicle regions tracks using matching methods of wavelet invariant moments bases to recognized object. To detect a moving object from image sequence the candidate regions detection phase uses an adaptive thresholding method between previous image and current image as result it was robust surroundings environmental change and moving object detections were possible. And by using wavelet features to recognize and tracking of vehicle, the proposed method decrease calculation time and not only it will be able to minimize the effect in compliance with noise of road image, vehicle recognition accuracy became improved. The result which it experiments from the image which it acquires from the general road image sequence and vehicle detection rate is 92.8%, the computing time per frame is 0.24 seconds. The proposed method can be efficiently apply to a real-time intelligence road traffic surveillance system.

• Journal of the Korean Institute of Telematics and Electronics
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• v.27 no.8
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• pp.1275-1283
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• 1990

Perception of surfaces from range images plays a key role in 3-D object recognition. Recognition of 3-D objects from range images is performed by matching the perceived surface descriptions with stored object models. The first step of the 3-d object recognition from range images is image segmentation. In this paper, an approach for segmenting 3-D range images into symbolic surface descriptions using spatial Gabor filter is proposed. Since the phase of data has a lot of important information, the phase information with magnitude information can effectively segment the range imagery into regions satisfying a common homogeneity criterion. The phase and magnitude of Gabor filter can represent a unique featur vector at a point of range data. As a result, range images are trnasformed into feature vectors in 3-parameter representation. The methods not only to extract meaningful features but also to classify a patch information from range images is presented.

• Proceedings of the Korean Society of Tribologists and Lubrication Engineers Conference
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• 1999.11a
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• pp.103-113
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• 1999

Point contact film thickness in elastohydrodynamic lubrication (EHL) is analyzed by the image processing method for the monochromatic incident light. Interference between the reflected lights both on Cr coating of glass disk and on super finished ball makes circular fringes, which are regarded as film thickness together with numbering of fringe order. In this study, we developed technology to measure the film thickness by analyzing dark and bright intensity waves which results from monochrome green light. Two typical fringe patterns only with intensity values 3re examined for the measurement of point contact EHL film thickness. We expect that this technology will give valuable clue to improve color image processing analysis for high resolution of EHL film thickness with white incident light.

• Journal of the Korea Institute of Military Science and Technology
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• v.24 no.4
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• pp.392-400
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• 2021

Unlike optical equipment, SAR(Synthetic Aperture Radar) has the advantage of obtaining images in all weather, and object detection in SAR images is an important issue. Generally, deep learning-based object detection was mainly performed in real-valued network using only amplitude of SAR image. Since the SAR image is complex data consist of amplitude and phase data, a complex-valued network is required. In this paper, a complex-valued ResNet network is proposed. SAR image object detection was performed by combining the ROI transformer detector specialized for aerial image detection and the proposed complex-valued ResNet. It was confirmed that higher accuracy was obtained in complex-valued network than in existing real-valued network.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.448-449
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• 2022

In the image upscaling field, the method using deep learning is showing better results than using the interpolation method. And for hologram upscaling, using deep learning is showing better results than general interpolation. In this paper, the network structure and learning results are analyzed. The learning results are compared by adjusting the depth of the network and the number of channels at the same weight.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.1
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• pp.95-101
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• 2007

Recently, two phase scheme for removing impulse noise in images is proposed. This algorithms first detect the noise candidates based on the adaptive median filter, and then apply optimizing techniques recursively only to those noise candidates to restore image. Thus the noise detector with high accuracy is important role on this algorithm, In this paper, novel noise detector is proposed, which can detect impose noise with high accuracy while reducing the probability of false detecting image details as impulses. And the method for reducing computational cost of regularization phase is presented also.

• Korean Journal of Optics and Photonics
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• v.16 no.6
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• pp.500-507
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• 2005

Two-dimensional (2D) images that are produced by terahertz (THz) irradiation we presented. It is possible to obtain 2D image of various materials by observing the amplitude and the phase of the THz signals which go through them. Better images are produced by combining the amplitude and phase of the signal rather than using only one of these. Homomorphic filtering that is one elf the well-known technique of digital image signal processing is effective to reduce the noise signal and can provide better quality images. The results can be applied to real-time imaging afterwards.