• Journal of Korea Multimedia Society
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• v.8 no.1
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• pp.19-26
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• 2005

The basis function of wavelet transform used in this paper is constructed by using lifting scheme, which is different from general wavelet transform. Lifting scheme is a new biorthogonal wavelet con-structing method, that does not use Fourier transform for constructing its basis function. In this paper, an image compression and reconstruction method using the lifting scheme was proposed. And this method improves data visualization by supporting a partial reconstruction and a local reconstruction. Approx- imations at various resolutions allow extracting various sizes of feature from an image or signal with a small amount of original information. An approximation with small size of scaling coefficients gives a brief outline of features at fast. Image compression and edge detection techniques provide good frame- works for data management and visualization in multimedia database.

• 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

• Journal of the Korean Institute of Telematics and Electronics B
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• v.29B no.11
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• pp.73-84
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• 1992

In this paper, an algorithm for recovering the 3-D shape from a single shaded image is proposed. In the proposed algorithm, by using the relation between the height and surface gradient (p, q), a set of linear equations is derived from the linearized reflectance function. Then the 3-D surface is recovered by employing the conjugate gradient technique. In order to improve the convergence speed of the solution, we also employ the hierarchical basis function and multiresolution images in the algorithm. A method for determining the regularization parameter, which is determined by trial and error in the conventional approach, is also introduced. In addition, the proposed algorithm attempts to recover the 3-D surface without requiring the boundary conditions, making it suitable for a real-time implementation. Simulation results for real image as well as synthetic image are provided to demonstrate the performance of the proposed algorithm.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.12
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• pp.2511-2519
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• 2009

In this paper, we introduce the methodological system design via feature selection using Principal Component Analysis and Particle Swarm Optimization algorithms. The overall methodological system design comes from three kinds of modules such as preprocessing module, feature extraction module, and recognition module. First, Histogram equalization enhance the quality of image by exploiting contrast effect based on the normalized function generated from histogram distribution values of 2D face image. Secondly, PCA extracts feature vectors to be used for face recognition by using eigenvalues and eigenvectors obtained from covariance matrix. Finally the feature selection for face recognition among the entire feature vectors is considered by means of the Particle Swarm Optimization. The optimized Polynomial-based Radial Basis Function Neural Networks are used to evaluate the face recognition performance. This study shows that the proposed methodological system design is effective to the analysis of preferred face recognition.

• Proceedings of the KSRS Conference
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• 1998.09a
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• pp.213-217
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• 1998

This study overviews existing evaluation methods of classification accuracy using confusion matrix proposed by Cohen in 1960's, and proposes ISDd(Index of Spatial Distribution by distance) and ISDs(Index of Spatial Distribution by scatteredness) for the evaluation of spatial distribution of satellite image classification errors, which has not been tried yet. Index of spatial distribution offers the basis of decision on adoption/rejection of classification results at sub-image level by evaluation of distribution, such as status of local aggregation of misclassified pixels. So, users can understand the spatial distribution of misclassified pixels and, can have the basis of judgement of suitability and reliability of classification results.

• The Transactions of the Korea Information Processing Society
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• v.4 no.8
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• pp.2133-2142
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• 1997

Compared with previous compression methods, fractal image compression drastically increases compression rate by using block-based encoding. Although decompression can be done in real time even with softwares, the most serious problem in utilizing the fractal method is the time required for the encoding. In this paper, we propose and verify i) an algorithm that reduces the encoding time by reducing the number of similarity searching on the basis of dimensional informations, and ii) an algorithm that enhances the quality of the restored image on the basis of brightness and contrast information. Finally, a method that enables fast compression with little quality degradation is proposed.

• Journal of the Korean Graphic Arts Communication Society
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• v.18 no.2
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• pp.1-12
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• 2000

This paper proposes a new algorithm classifing same hues in order toe estimate the spectral reflectance of object from 3 band color image information. To estimate the spectral reflectance of object, the conventional estimation methods are required of 5 or 9 band digital color values. The 5 or 9 band image acquisition systems are required of 5 or 3 times same work for color image acquisition process. To solve the above problems, we propose a new method that can be estimated spectra reflectance estimation of object. The proposed method is to classify same hues corresponding a color stimulus, by using hue angle and chroma vector of a color stimulus. The classified same hues are used as the population corresponding a color stimulus. The range of same hue is estimated by the cumulative proportional ration according to the number of basis function.

• Journal of Korean Academy of Nursing Administration
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• v.7 no.3
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• pp.455-472
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• 2001

The purpose of this study was to serve as a basis for mapping out successful strategies to build the professional self-image of nurses through uniform, by examining their satisfaction with uniform and professional self-image by general characteristics, and identifying the correlational relationship between the two factors. The subjects in this study were 205 nurses who served in general departments of two university hospitals in Seoul. The departments where special uniform was required, including ICU, RR, OR and CSR, were excluded. The data were collected from September 15 through 22, 2000. For measurement of uniform satisfaction level, a uniform satisfaction scale was prepared by myself, and Arthur(1990)'s PSCNI translated and modified by Song Kyong Ae and Rho Chun Hee(1996) was employed. The Cronbach a of the uniform satisfaction scale and PSCNI was 0.90 and 0.86 respectively. The collected data were analyzed by SAS, and real number, percentage, average and standard deviation were calculated. Besides, t-test, one-way ANOVA, Pearson's r procedures were utilized, and Scheffe test was conducted as a posttest. The findings of this study were as below: 1. The uniform satisfaction of the nurses investigated was scored 2.52 on the basis of 4 points, which was on the medium level. By subarea, symbolicity satisfaction was 2.48, and aesthetic satisfaction was 2.60. The functionability satisfaction was 2.44. So the esthetic satisfaction was greatest. 2. Among general characteristics of the subjects, two factors made a significant difference to their uniform satisfaction : age(F=4.05, P=.0189), and total career(F=4.25, P=.0061). 3. Their professional self-image got 2.75 on the basis of 4 points, which was on upper middle level. The subarea score was 2.79 for professional work, 2.52 for satisfaction and 2.97 for communication. The communication area was rated highest, and the satisfaction area was scored lowest. 4. Among the general characteristics of the subjects, professional self-image was different according to five factors : age(F=17.83, P=.001), marital status(T=5.18, P=.0000), educational background(F=8.72, P=.0002), position(T=-5.29, P=.0000) and total career(F=15.23, p=.0001). Better professional self-image was possessed by the older group than the younger one, by the married group than the singles, by the better-educated group than the less-educated, by the nurses in position equal to or higher than charge nurse, or by the higher-career group. 5. The correlational relationship of uniform satisfaction to professional self-image was statistically significant, yet very weak(r=.1978, p=.0045). The satisfaction area of professional self-image was correlated to every uniform satisfaction area, including symbolicity(4=.4393, p=.0001), aesthetics(r=.2471, p=.0004), functionability(r=.3094, p=.0001) and total satisfaction(r=.4050, p=.0001). Therefore, the uniform satisfaction gave an impact on the satisfaction area of professional self-image of the nurses, and there was a significant correlational relationship between uniform symbolicity area and total professional self-image(r=.2416, p=.0005).

• Proceedings of the Korean Institute of Communication Sciences Conference
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• 1984.04a
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• pp.13-17
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• 1984

A hybrid version of the Hadamard and center Line Symmetric Haar Transform called H-CLSH is defined and developed. Efficient algorithms for fast computation of the H-CLSH and its inverse are developed. The H-CLSH is applied to digital signal and image processing and its utility and image processing and its utility and effectiveness are compared with Hadamard-Haar discrete transforms on the basis of some standard performance criteria.

• Journal of Korea Technical Association of The Pulp and Paper Industry
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• v.31 no.3
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• pp.105-109
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• 1999

The purpose of this experiment was to see the effect of local basis weight on the local strain during changing moisture content in handsheets. The averaged strain value of the whole size of paper sheet did not give more valuable information to explain non uniform deformation in the paper sheet. The combination of intact strain measurement system KISA (Linear Image Strain Analysis) and local basis weight measurement method using a scanner made it possible to compare local basis weight with local strain to explain moisture induced paper deformation . Usually higher basis weight local area showed higher moisture induced local strain. However, the hygro-induced strain values were highly affected by the behavior of neighbor local areas. Well distributed local basis weight paper would give more uniform local strains than those of non-uniformed local basis weight paper.