• The Transactions of The Korean Institute of Electrical Engineers
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• v.64 no.9
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• pp.1347-1355
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• 2015

In this study, we compare the recognition performance using PCA and RBFNNs for introducing robust face recognition system to pose variations based on pose estimation. proposed face recognition system uses Honda/UCSD database for comparing recognition performance. Honda/UCSD database consists of 20 people, with 5 poses per person for a total of 500 face images. Extracted image consists of 5 poses using Multiple-Space PCA and each pose is performed by using (2D)²PCA for performing pose classification. Linear polynomial function is used as connection weight of RBFNNs Pattern Classifier and parameter coefficient is set by using Particle Swarm Optimization for model optimization. Proposed (2D)²PCA-based face pose classification performs recognition performance with PCA, (2D)²PCA and RBFNNs.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.64 no.7
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• pp.1064-1073
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• 2015

In this study, we introduce the pedestrian detection system by using the feature of HOG-PCA and RBFNNs pattern classifier. HOG(Histogram of Oriented Gradient) feature is extracted from input image to identify and recognize a object. And a dimension is reduced for improving performance as well as processing speed by using PCA which is a typical dimensional reduction algorithm. So, the feature of HOG-PCA through the dimensional reduction by using PCA leads to the improvement of the detection rate. FCM clustering algorithm is used instead of gaussian function to apply the characteristic of input data as well and connection weight is used by polynomial expression such as constant, linear, quadratic and modified quadratic. Finally, INRIA person database known as one of the benchmark dataset used for pedestrian detection is applied for the performance evaluation of the proposed classifier. The experimental result of the proposed classifier are compared with those studied by Dalal.

• Archives of design research
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• v.16 no.1
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• pp.159-168
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• 2003

Modern fashion shop is changed by the changing of fashion style. And as purchasing pattern is changed to consuming pattern which has strong individuality, functions as space which reflet characteristics of products and consumers in order to present sensitive and individual image are also required, besides conventional concept as space which simply focused on sale. Meanwhile, in the 1980's, the fashion presented retro mood modernly by popularization of post-modernism and introduced minimalism that is one of the anti-cultures in the 1960's. Recently minimalistic trends which are expressed by various attempts and a new point of view are introduced to the fashion shop by interior designer. Therefore, in this study, minimalistic characteristics which appear in the composition of interior space of the modern fashion shop are researched by theoretical consideration and analysis of examples and consistent direction of fashion shop is presented.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.7 no.2
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• pp.200-205
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• 2006

Abstract This paper presents a personal identification method based on BMME and LDA for images acquired at anterior and posterior occlusion expression of teeth. The method consists of teeth region extraction, BMME, and pattern recognition forthe images acquired at the anterior and posterior occlusion state of teeth. Two occlusions can provide consistent teeth appearance in images and BMME can reduce matching error in pattern recognition. Using teeth images can be beneficial in recognition because teeth, rigid objects, cannot be deformed at the moment of image acquisition. In the experiments, the algorithm was successful in teeth recognition for personal identification for 20 people, which encouraged our method to be able to contribute to multi-modal authentication systems.

• Journal of the Korean Society for Precision Engineering
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• v.17 no.1
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• pp.129-137
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• 2000

In this paper, a new method of noncontact measurement has been developed for a 3 dimensional topography in semiconductor wafer, implementing a new optical probe based on the precision defocus measurement. The developed technique consists of the new optical probe, precision stages, and the measurement/control system. The basic principle of the technique is to use the reflected slit beam from the specimen surface, and to measure the deviation of the specimen surface. The defocusing distance can be measured by the reflected slit beam, where the defocused image is measured by the proposed optical probe, giving very high resolution. The distance measuring formula has been proposed for the developed probe, using the laws of geometric optics. The precision calibration technique has been applied, giving about 10 nanometer resolution and 72 nanometer of four sigma uncertainty. In order to quantitize the micro pattern in the specimen surface, some efficient analysis algorithms have been developed to analyse the 3D topography pattern and some parameters of the surface. The developed system has been successfully applied to measure the wafer surface, demonstrating the line scanning feature and excellent 3 dimensional measurement capability.

• Journal of the Korean Society for Precision Engineering
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• v.21 no.11
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• pp.69-74
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• 2004

This paper presents ESPI system for the measurement of thermal expansion coefficient of STS430 up to 1,00$0^{\circ}C$ . Existing methods, strain gauge and moire have the limitation of contact to object and do not supply the coefficient up to 80$0^{\circ}C$ . There needs to measure the data up to 80$0^{\circ}C$, because heat resistant materials have high melting temperature up to 1,000'E In previous studies related to thermal strain analysis, the quantitative results have not reported by ESPI at high temperature, yet. In-plane ESPI and vacuum chamber for the reduction of air turbulence and oxidation are designed for the measurement of the coefficient up to 1,00$0^{\circ}C$ and speckle correlation fringe pattern images are processed by commercial image filtering tool-smoothing, thinning and enhancement- to obtain quantitative results, which is compared with references data. The comparison shows two data are agreed within 4.1% blow $600^{\circ}C$ however, there is some difference up to $600^{\circ}C$. Also, the incremental ratio of the coefficient is changed up to 80$0^{\circ}C$ . The reason is the phase transformation of STS430 probably begins at 80$0^{\circ}C$

• Transactions of the Korean Society of Mechanical Engineers A
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• v.21 no.1
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• pp.1-11
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• 1997

Austomated visual inspection(AVI) capability has become an important key component in the automated manufacturing system. In such a visual inspection system an intensity(or color) image of a scene is quickly affected by optical property of objects, condition and roughness of surface, lens and filters, image sensor property and lighting system. In particular, the lighting system disign is the most important factor, since it affects overall performance of the visual system. For fast and cheap automated visual inspection system it is important to obtain the good image quality which results from careful attention to the design of the lighting system. In this paper, the lighting subsystem of AVI system is analysed for the inspection of printed circuit board(PCB) patterns. The spectral reflectance of materials, which are composed of PCB, is measured for choosing the light source. The reflection property is theoretically obtained by a reflection model and also obtained by experiments which measure intensity with varying the viewing direction of image sensor and the lighting direction of illuminator. The illumination uniformity of a ring-type illuminator. The lighting system is designed based upon the experimental results and theoretial analysis.

• Journal of Biomedical Engineering Research
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• v.33 no.4
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• pp.169-176
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• 2012

Tumor cell morphology is closely related to its migratory behaviors. An active tumor cell has a highly irregular shape, whereas a spherical cell is inactive. Thus, quantitative analysis of cell features is crucial to determine tumor malignancy or to test the efficacy of anticancer treatment. We use 3D time-lapse phase-contrast microscopy to analyze single cell morphology because it enables to observe long-term activity of living cells without photobleaching and phototoxicity, which is common in other fluorescence-labeled microscopy. Despite this advantage, there are image-level drawbacks to phase-contrast microscopy, such as local light effect and contrast interference ring. Therefore, we first corrected for non-uniform illumination artifacts and then we use intensity distribution information to detect cell boundary. In phase contrast microscopy image, cell is normally appeared as dark region surrounded by bright halo ring. Due to halo artifact is minimal around the cell body and has non-symmetric diffusion pattern, we calculate cross sectional plane which intersects center of each cell and orthogonal to first principal axis. Then, we extract dark cell region by analyzing intensity profile curve considering local bright peak as halo area. Finally, we calculated the Fourier descriptor that morphological characteristics of cell to classify tumor cells into active and inactive groups. We validated classification accuracy by comparing our findings with manually obtained results.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.10
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• pp.5015-5038
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• 2018

In this paper, a novel spectral-spatial joint sparse representation algorithm for hyperspectral image classification is proposed based on multi-layer superpixels in various scales. Superpixels of various scales can provide complete yet redundant correlated information of the class attribute for test pixels. Therefore, we design a joint sparse model for a test pixel by sampling similar pixels from its corresponding superpixels combinations. Firstly, multi-layer superpixels are extracted on the false color image of the HSI data by principal components analysis model. Secondly, a group of discriminative sampling pixels are exploited as reconstruction matrix of test pixel which can be jointly represented by the structured dictionary and recovered sparse coefficients. Thirdly, the orthogonal matching pursuit strategy is employed for estimating sparse vector for the test pixel. In each iteration, the approximation can be computed from the dictionary and corresponding sparse vector. Finally, the class label of test pixel can be directly determined with minimum reconstruction error between the reconstruction matrix and its approximation. The advantages of this algorithm lie in the development of complete neighborhood and homogeneous pixels to share a common sparsity pattern, and it is able to achieve more flexible joint sparse coding of spectral-spatial information. Experimental results on three real hyperspectral datasets show that the proposed joint sparse model can achieve better performance than a series of excellent sparse classification methods and superpixels-based classification methods.

• KIPS Transactions on Software and Data Engineering
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• v.9 no.2
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• pp.69-76
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• 2020

In this paper, we introduce a method to visualize the contrast diffusion patterns and the dynamic vascular patterns in a contrast-enhanced ultrasound image sequence. We present an imaging technique to visualize parameters such as contrast arrival time, peak intensity time, and contrast decay time in contrast-enhanced ultrasound data. The contrast flow pattern and its velocity are important for characterizing focal liver lesions. We propose a method for representing the contrast diffusion patterns as an image. In the methods, respiratory motion may degrade the accuracy of the parametric images. Therefore, we present a respiratory motion tracking technique that uses dynamic weights and a momentum factor with respect to the respiration cycle. Through the experiment using 72 CEUS data sets, we show that the proposed method makes it possible to overcome the limitation of analysis by the naked eye and improves the reliability of the parametric images by compensating for respiratory motion in contrast-enhanced ultrasonography.