• Journal of Information Processing Systems
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• v.18 no.1
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• pp.48-58
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• 2022

Blind restoration for motion-blurred images is always the research hotspot, and the key for the blind restoration is the accurate blur kernel (BK) estimation. Therefore, to achieve high-quality blind image restoration, this thesis presents a novel windowed-total-variation method. The proposed method is based on the spatial scale of edges but not amplitude, and the proposed method thus can extract useful image edges for accurate BK estimation, and then recover high-quality clear images. A large number of experiments prove the superiority.

• Journal of the Korean Society of Clothing and Textiles
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• v.24 no.8
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• pp.1177-1186
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• 2000

The Study was consist of clothing shape(H-line, A-line, V-line, X-line, O-line) and color(Blace, Grey1, Grey2, White). The main purpose of this study is to analyze image differences due to shape variation, image differences due to observers characteristic differences. The main findings can be summarized as follow. First, image differences due to shape variation are statistically significant ar five factors - the maturity level, the degree of softness, attractiveness, the degree of recognition, and the activity. But the degree of recognition is found out to be the least significant factor. H-line is estimated the mature image, A·X-line is estimated young, feminine and active image. Second, image differences by observers characteristics are various depending on the shape of clothing.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.5 no.11
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• pp.2160-2174
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• 2011

In this paper, a new technique for color reproduction based on color variation characteristics of digital camera under a dim light condition is proposed. Generally, photographers should adjust a camera exposure properly for obtaining an image with real color tone of subjects. Thus, in case of taking a picture under a dim light condition, the exposure time of a camera has to be relatively longer than the one under a bright light condition. Although images with real color tone of the subject are obtained, the images may get blurred due to the shaky hands of photographer holding the camera. In order to avoid the blur effect, an input image is captured from a camera set as a short exposure time under a dim light condition. Then we propose a method to reproduce color tone of the dim input image. To this end, color variation characteristics which represent color variations of a digital camera are first extracted by analyzing the Macbeth color checker images taken under various exposure values. Then, a color reproduction is performed by an estimation based on the color variation characteristics. Experimental results have shown that the proposed method has achieved better performance of color reproduction, compared with existing methods.

• Journal of Microbiology and Biotechnology
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• v.33 no.3
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• pp.348-355
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• 2023

Epifluorescence microscopy with image analysis was evaluated as a biofilm quantification method (i.e., quantification of surface area colonized by biofilms), in comparison with crystal violet (CV) staining. We performed different experiments to generate multispecies biofilms with natural and artificial bacterial assemblages. First, four species were inoculated daily in 16 different sequences to form biofilms (surface colonization, 0.1%-56.6%). Second, a 9-species assemblage was allowed to form biofilms under 10 acylase treatment episodes (33.8%-55.6%). The two methods comparably measured the quantitative variation in biofilms, exhibiting a strong positive relationship (R² ≥ 0.7). Moreover, the two methods exhibited similar levels of variation coefficients. Finally, six synthetic and two natural consortia were allowed to form biofilms for 14 days, and their temporal dynamics were monitored. The two methods were comparable in quantifying four biofilms colonizing ≥18.7% (R² ≥ 0.64), but not for the other biofilms colonizing ≤ 3.7% (R² ≤ 0.25). In addition, the two methods exhibited comparable coefficients of variation in the four biofilms. Microscopy and CV staining comparably measured the quantitative variation of biofilms, exhibiting a strongly positive relationship, although microscopy cannot appropriately quantify the biofilms below the threshold colonization. Microscopy with image analysis is a promising approach for easily and rapidly estimating absolute quantity of multispecies biofilms.

• Journal of the Korean Institute of Intelligent Systems
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• v.24 no.5
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• pp.504-511
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• 2014

This paper presents a hybrid recognition method, which is based on the nonlinear histogram equalization and the multidimensional intensity variation of an images. The nonlinear histogram equalization based on a adaptively modified function is applied to improve the quality by adjusting the brightness of the image. The multidimensional intensity variation by considering the a extent of 4-step changes in brightness between the adjacent pixels is also applied to reflect accurately the attributes of image. The statistical correlation that is measured by the normalized cross-correlation(NCC) coefficient, is applied to comprehensively measure the similarity between the images. The NCC is considered by the intensity variation of each 2-direction(x-axis and y-axis) image. The proposed method has been applied to the problem for recognizing the 50-face images of 40*40 pixels. The experimental results show that the proposed method has a superior recognition performances to the method without performing the histogram equalization, or the linear histogram equalization, respectively.

• The Journal of the Korea Contents Association
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• v.6 no.4
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• pp.11-18
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• 2006

A new algorithm for removing salt and pepper impulse noise in image using impulse noise detector and total variation optimization is presented. The proposed two types of noise detectors which are based on the adaptive median filter, can detect impulse noise with high accuracy while reducing the probability of detecting image details as impulses. And the detectors maintain its performance independent of noise density. For removing impulses, total variation optimization is applied only to those detected noise candidate to reduces unnecessary computation. The proposed approach successfully remove impulse noise while preserving image details.

• Journal of the Korean Society of Radiology
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• v.13 no.5
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• pp.773-778
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• 2019

Images using X-rays are essential to diagnosis, but noise is inevitable in the image. To compensate for this, a total variation (TV) algorithm was presented to reduce the patient's exposure dose while increasing the quality of the images. The purpose of this study is to verify the effect on the image quality in radiographic imaging according to the thickness of the additional filtration plate through simulation, and to evaluate the usefulness of the TV algorithm. By using the Geant4 Application for Tomographic Emissions (GATE) simulation image, the actual size, shape and material of the Polymethylmethacrylate (PMMA) phantom were identical, the contrast to noise ratio (CNR) and coefficient of variation (COV) were compared. The results showed that the CNR value was the highest and the COV the lowest when applying the TV algorithm. In addition, we can acquire superior CNR and COV results with 0 mm Al in all algorithm cases.

• ETRI Journal
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• v.37 no.6
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• pp.1251-1258
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• 2015

We investigate an image recovery method for sparse-view computed tomography (CT) using an iterative shrinkage algorithm based on a second-order approach. The two-step iterative shrinkage-thresholding (TwIST) algorithm including a total variation regularization technique is elucidated to be more robust than other first-order methods; it enables a perfect restoration of an original image even if given only a few projection views of a parallel-beam geometry. We find that the incoherency of a projection system matrix in CT geometry sufficiently satisfies the exact reconstruction principle even when the matrix itself has a large condition number. Image reconstruction from fan-beam CT can be well carried out, but the retrieval performance is very low when compared to a parallel-beam geometry. This is considered to be due to the matrix complexity of the projection geometry. We also evaluate the image retrieval performance of the TwIST algorithm -sing measured projection data.

• Progress in Medical Physics
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• v.23 no.4
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• pp.252-260
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• 2012

The reduction of radiation dose from x-ray is a main concern in computed tomography (CT) imaging due to the side-effect of the dose on human body. Recently, the various methods for dose reduction have been studied in CT and one of the method is a iterative reconstruction based on total variation (TV) minimization at few-views data. In this paper, we evaluated the image quality between total variation (TV) minimization algorithm and Feldkam-Davis-kress (FDK) algorithm in micro computed tomography (CT). To evaluate the effect of TV minimization algorithm, we produced a cylindrical phantom including contrast media, water, air inserts. We can acquire maximum 400 projection views per rotation of the x-ray tube and detector. 20, 50, 90, 180 projection data were chosen for evaluating the level of image restoration by TV minimization. The phantom and mouse image reconstructed with FDK algorithm at 400 projection data used as a reference image for comparing with TV minimization and FDK algorithm at few-views. Contrast-to-noise ratio (CNR), Universal quality index (UQI) were used as a image evaluation metric. When projection data are not insufficient, our results show that the image quality of reconstructed with TV minimization is similar to reconstructed image with FDK at 400 view. In the cylindrical phantom study, the CNR of TV image was 5.86, FDK image was 5.65 and FDK-reference was 5.98 at 90-views. The CNR of TV image 0.21 higher than FDK image CNR at 90-views. UQI of TV image was 0.99 and FDK image was 0.81 at 90-views. where, the number of projection is 90, the UQI of TV image 0.18 higher than FDK image at 90-views. In the mouse study UQI of TV image was 0.91, FDK was 0.83 at 90-views. the UQI of TV image 0.08 higher than FDK image at 90-views. In cylindrical phantom image and mouse image study, TV minimization algorithm shows the best performance in artifact reduction and preserving edges at few view data. Therefore, TV minimization can potentially be expected to reduce patient dose in clinics.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.64 no.7
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• pp.1104-1113
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• 2015

In this paper, we propose Two-Dimensional Robust Face Recognition System Realized with the Aid of Facial Symmetry with Illumination Variation. Preprocessing process is carried out to obtain mirror image which means new image rearranged by using difference between light and shade of right and left face based on a vertical axis of original face image. After image preprocessing, high dimensional image data is transformed to low-dimensional feature data through 2-directional and 2-dimensional Principal Component Analysis (2D)2PCA, which is one of dimensional reduction techniques. Polynomial-based Radial Basis Function Neural Network pattern classifier is used for face recognition. While FCM clustering is applied in the hidden layer, connection weights are defined as a linear polynomial function. In addition, the coefficients of linear function are learned through Weighted Least Square Estimation(WLSE). The Structural as well as parametric factors of the proposed classifier are optimized by using Particle Swarm Optimization(PSO). In the experiment, Yale B data is employed in order to confirm the advantage of the proposed methodology designed in the diverse illumination variation