• Journal of the Korean Graphic Arts Communication Society
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• v.22 no.1
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• pp.9-18
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• 2004

Recently as color image processing to be become independent have been desired at the light source in an image processing and it have been enlarged. An image processing of the light source which is become independent means an image processing which uses a spectral reflectance information. We improved it in the spectral reflectance estimation method which uses existing 3-band image in this research that the improvement of an identity color population generation method which uses the hue angle and the processing speed improvement and introduces a labelling method. The precision of a spectral reflectance estimation appeared to the ${\Delta}E^*_{ab}$ of an average 2.7 comparing with the measurement price. The practical use possibility came to be fast and appeared a processing speed compared with existing method.

• Proceedings of the IEEK Conference
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• 2008.06a
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• pp.863-864
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• 2008

To predict the iris matching performance and guarantee its reliability, image quality measure prior to matching is desired. An analysis on iris image degradation factors which deteriorate matching performance is a basic step for iris image quality measure. We considered five degradation factors-white-out, black-out, noise, blur, and occlusion by specular reflection-which happen generally during the iris image acquisition process. Experimental results show that noise and white-out degraded the EER most significantly, while others on EER were either insignificant or degradation images resulted in even better performance in some cases of blur. This means that degradation factors that affect the performance can be different from those based on human perception or image degradation evaluation.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.36 no.11
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• pp.1463-1471
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• 2012

In this study, a 3-axis camera system design is proposed for application to an existing 2-axis surveillance robot. A camera-image-based target-tracking algorithm for this robot has also been proposed. The algorithm has been validated using a virtual simulation. In the algorithm, the heading direction vector of the camera system in the mobile surveillance robot is obtained by the position error between the center of the view finder and the center of the object in the camera image. By using the heading direction vector of the camera system, the desired pan and tilt angles for target-tracking and the desired roll angle for the stabilization of the camera image are obtained through inverse kinematics. The algorithm has been validated using a virtual simulation model based on MATLAB and ADAMS by checking the corresponding movement of the robot to the target motion and the virtual image error of the view finder.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.10
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• pp.5129-5152
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• 2016

Multi-view super-resolution (MVSR) aims to estimate a high-resolution (HR) image from a set of low-resolution (LR) images that are captured from different viewpoints (typically by different cameras). MVSR is usually applied in camera array imaging. Given that MVSR is an ill-posed problem and is typically computationally costly, we super-resolve multi-view LR images of the original scene via image fusion (IF) and blind deblurring (BD). First, we reformulate the MVSR problem into two easier problems: an IF problem and a BD problem. We further solve the IF problem on the premise of calculating the depth map of the desired image ahead, and then solve the BD problem, in which the optimization problems with respect to the desired image and with respect to the unknown blur are efficiently addressed by the alternating direction method of multipliers (ADMM). Our approach bridges the gap between MVSR and BD, taking advantages of existing BD methods to address MVSR. Thus, this approach is appropriate for camera array imaging because the blur kernel is typically unknown in practice. Corresponding experimental results using real and synthetic images demonstrate the effectiveness of the proposed method.

• Journal of Korea Multimedia Society
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• v.19 no.9
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• pp.1679-1689
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• 2016

Recently, due to the rapid development of multimedia technologies, as image data has been extensive and large-scaled, the problem of increasing the time needed to retrieve the desired image is gradually critical. Image retrieval system that allows users to quickly and accurately search for the desired image information has been researched for a long time. However, in the case of content-based image retrieval representative Color Histogram, Color Coherence Vectors (CCV), Scale Invariant Feature Transform (SIFT) used in sensitive to changes in brightness, rotation, there is a problem that can occur misrecognized division off the power. In this paper, in order to evaluate the video retrieval system proposed, no change in brightness, respectively 0°, 90°, 180°, 270° rotated brightness up based on the case of changing, when the brightness down the results were compared with the performance evaluation of the system is an average of about 2% to provide the difference in performance due to changes in brightness, color histogram is an average of about 12.5%, CCV is an average of about 12.25%, it appeared in the SIFT is an average of about 8.5%, Thus, the proposed system of the variation width of the smallest in average about 2%, was confirmed to be robust to changes in the brightness and rotation than the existing systems.

• The Magazine of the IEIE
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• v.38 no.1
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• pp.31-43
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• 2011

The mathematical foundations of the compressive sensing which goes against the common wisdom of data acquisition (the Nyquist-Shannon theorem) is reviewed. The compressive sensing asserts that one can reconstruct images or signals of interest accurately from a number of samples far smaller than the desired resolution of the image (e.g., the number of pixels in the image). The compressive sensing has far reaching implications. It suggests the new data acquisition protocols that translates analog information to digital form with fewer sensors considered necessary.

• Journal of the Korean Society of Fashion and Beauty
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• v.3 no.2 s.2
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• pp.31-38
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• 2005

Make-up changes facial images. In particular, eyebrow make-up is a part of changing expression most easily and effectively. While color make-up is helpful to produce women's desired image with their favorite colors, eyebrow make-up is hidden actor to give a clear impression to others. Therefore, this study connected facial type which is an important factor deciding facial image with eyebrow, examined image of eyebrow make-up and that changed by facial types and aimed to be helpful in producing more effective facial image with eyebrow make-up considering one's facial type. Consequently, it was found that eyebrow make-up was a great factor in making better facial impression and image and complementing the weakness of facial type. h strong impression of facial type can be changed into soft shape or foolish shape in worse case depending on the types of eyebrow make-up. Eyebrow make-up shows charming image as angle of eyebrow is steep, heavy image as eyebrow is horizontal, cold image as eyebrow tail rises and simple and dull image as it lowers. Therefore, it is known that image of eyebrow make-up can be governed by several factors including angle and direction of eyebrow. Consequently, it is thought that most effective eyebrow make-up considers individual facial types, images of their eyes, noses and mouths and factors deciding angle, direction and colors of eyebrow.

• Journal of Information Processing Systems
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• v.5 no.1
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• pp.1-4
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• 2009

Level set methods are the numerical techniques for tracking interfaces and shapes. They have been successfully used in image segmentation. A new variational level set evolving algorithm without re-initialization is presented in this paper. It consists of an internal energy term that penalizes deviations of the level set function from a signed distance function, and an external energy term that drives the motion of the zero level set toward the desired image feature. This algorithm can be easily implemented using a simple finite difference scheme. Meanwhile, not only can the initial contour can be shown anywhere in the image, but the interior contours can also be automatically detected.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 1995.06a
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• pp.83-86
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• 1995

Many image display devices allow only a limited number of colors to be simultaneously displayed. In displaying of natural color image using color palette, it is necessary to construct an optimal color palette and map each pixel of the original image to a color palette with fast. In this paper, we proposed the clustering algorithm using local region block centered one color cluster in the prequantized 3-D histogram. Cluster pairs which have the least distortion error are merged by considering distortion measure. The clustering process is continued until to obtain the desired number of colors. Same as the clustering process, original color image is mapped to palette color via a local region block centering around prequantized original color value. The proposed algorithm incorporated with a spatial activity weighting value which is smoothing region. The method produces high quality display images and considerably reduces computation time.

• Journal of the Korean Institute of Telematics and Electronics A
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• v.31A no.6
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• pp.61-69
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• 1994

For distortion-invariant recognition of Korean characters, a holographic implementation of an optical associative memory system is proposed. The structure of the proposed system is a single-layer neural network employing interconneclion matrix, thresholding and feedback. To provide the interconnection matrix, we use two CGII's which are placed on intermcdiate plane of cascaded Vander Lugt corrclators to form an optical memory loop. The holographic correlator stores reference images in a hologram and retrives them in a coherently illuminated feedback loop. An input image which maybe noisy or incomplete, is applicd to the system and simultaneously correlated optically with all of the stord images. These correlations are throsholed and fed back to the input, where the strongest correlation reinforces the input image. The enhanced image passes arround the loop repeatedly, approaching the stored image more closely on each pass until the system stabilizes on the desired image. The computer simulation results show that the proposed Korean Character recognition algorithm has high discrimination capability and noise immunity.