• Journal of the Korean Institute of Intelligent Systems
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• v.11 no.5
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• pp.406-412
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• 2001

In this paper, a new fuzzy single layer learning algorithm is proposed, which shows improved learning time and convergence property than that of the conventional fuzzy single layer perceptron algorithms. First, we investigate the structure of physiological neurons of the nervous system and propose new neuron structures based on fuzzy logic. And by using the proposed fuzzy neuron structures, the model and learning algorithm of Physiological Fuzzy Single Layer Perceptron(P-FSLP) are proposed. For the evaluation of performance of the P-FSLP algorithm, we applied the conventional fuzzy single layer perceptron algorithms and the P-FSLP algorithm to three experiments including Exclusive OR problem, the 3-bit parity bit problem and the recognition of car licence plates, which is an application of image recognition, and evaluated the performance of the algorithms. The experimentation results showed that the proposed P-FSLP algorithm reduces the possibility of local minima more than the conventional fuzzy single layer perceptrons do, and enhances the time and convergence for learning. Furthermore, we found that the P-FSLP algorithm has the great capability for image recognition applications.

• Journal of the Korea Society of Computer and Information
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• v.24 no.11
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• pp.71-78
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• 2019

Most 3D displays that are currently in the market adopt the binocular disparity method creating a different image for the left and right eye for a 3 dimensional effect. However, commercialized 3D image output devices lack in performance making it uncomfortable for the viewer and restrict the viewer to certain positions. In this paper, we propose a single-cell polarized lens type stereoscopic system which has a smaller viewing angle and reduced crosstalk, with improved light penetration compared to existing double-cell structures; and analyzed the single-cell polarized lens type stereoscopic system properties, and conducted an effect analysis of performance improvement compared to the dual-cell type. Results showed that the single-cell type had a 25% improved performance, and the 3D crosstalk index which is an important index for quality characteristics of stereoscopic systems, increased over about 37%, compared to the dual-cell type.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10b
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• pp.520-525
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• 1992

This paper reports several mathematical properties of the filter vector developed for processing linearly-additive spatially-invariant image sequences. In this filtering of an image sequence into a single filtered image, the information about the image components originally distributed over the entire sequence is compressed into the one new image in a way that the desired component is enhanced and the undesired (interfering) components and noise are suppressed.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.31 no.7
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• pp.490-495
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• 2018

A multielectrode electronic paper film capable of expressing a single-color image was fabricated by injecting color electronic ink into an electronic paper panel; on the basis of its reflective or transparent properties, it is possible to control the expression of six single-color images and their transmittance. In this study, a single-color image was represented by driving a multielectrode electronic paper film; color coordinates were measured. The six capable single colors were yellowish pink (0.444, 0.354), white (0.355, 0.352), black (0.241, 0.241), orange (0.514, 0.360), reddish orange (0.606, 0.338), and reddish purple (0.469, 0.145). Color particles used in this paper were black and white, by which six colors are accomplished, but more single-color images can be combined by using cyan, magenta, and yellow particles.

• Journal of Digital Contents Society
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• v.18 no.8
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• pp.1635-1640
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• 2017

In this paper, a hierarchical image tree model for weather classification is defined in a single outdoor image, and a weather classification algorithm using image intensity and k-mean segmentation image is proposed. In the first level of the hierarchical image tree model, the indoor and outdoor images are distinguished. Whether the outdoor image is daytime, night, or sunrise/sunset image is judged using the intensity and the k-means segmentation image at the second level. In the last level, if it is classified as daytime image at the second level, it is finally estimated whether it is sunny or foggy image based on edge map and fog rate. Some experiments are conducted so as to verify the weather classification, and as a result, the proposed method shows that weather features are effectively detected in a given image.

• International journal of advanced smart convergence
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• v.9 no.3
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• pp.118-126
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• 2020

In this paper, we present an effective single image fog removal by using the Joint Bright and Dark Channel (JBDC) and pixel-based transmission estimation to enhance the visibility of outdoor images susceptible to degradation due to weather and environmental conditions. The conventional methods include refinement process of coarse transmission with heavy computational complexity. The proposed transmission estimation reveals excellent edge-preserving performance and does not require the refinement process. We estimate the atmospheric light in pixel-based fashion, which can improve the transmission estimation performance and visual quality of the restored image. Moreover, we propose an adaptive transmission estimation to enhance the visual quality specifically in sky regions. Comprehensive experiments on various fog images show that the proposed method exhibits reduced computational complexity and excellent fog removal performance, compared with the existing methods; thus, it can be applied to various fields including real-time devices.

• 한국정보디스플레이학회:학술대회논문집
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• 2006.08a
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• pp.294-297
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• 2006

Using a single LC panel and two lighting systems, we have developed an advanced LCD system called "Double-Sided LCD." It has only one LC panel and two lighting systems, but it can display images of the same size and resolution on both the front and the rear side. Furthermore, utilizing a simple and thin lighting system we have reduced dramatically its module thickness up to 3.0mm, much thinner than that of conventional dual-type LCD, which is quite appropriate for the use of mobile applications.

• Journal of the Korea Society of Computer and Information
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• v.22 no.3
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• pp.45-51
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• 2017

In this paper, we propose a consecutive-frame super-resolution method to tackle a moving object problem. The super-resolution is a method restoring a high resolution image from a low resolution image. The super-resolution is classified into two types, briefly, single-frame super-resolution and consecutive-frame super-resolution. Typically, the consecutive-frame super-resolution recovers a better than the single-frame super-resolution, because it use more information from consecutive frames. However, the consecutive-frame super-resolution failed to recover the moving object. Therefore, we proposed an improved method via moving object detection. Experimental results showed that the proposed method restored both the moving object and the background properly.

• Proceedings of the IEEK Conference
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• 2003.07e
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• pp.2012-2015
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• 2003

This paper proposes a pose-invariant face recognition method using cylindrical model and stereo camera. We divided this paper into two parts. One is single input image case, the other is stereo input image case. In single input image case, we normalized a face's yaw pose using cylindrical model, and in stereo input image case, we normalized a face's pitch pose using cylindrical model with estimated object's pitch pose by stereo geometry. Also, since we have advantage that we can utilize two images acquired at the same time, we can increase overall recognition rate by decision-level fusion. By experiment, we confirmed that recognition rate could be increased using our methods.

• Annual Conference of KIPS
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• 2019.05a
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• pp.525-528
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• 2019

Atmospheric particle removal is a challenging task and attacks wide interests in computer vision filed. In this paper, we proposed a single image snow removal framework based on deep residual networks. According to the fact that there are various snow sizes in a snow image, the inception module which consists of different filter kernels was adopted to extract multiple resolution features of the input snow image. Except the traditional mean square error loss, the perceptual loss and total variation loss were employed to generate more clean images. Experimental results on synthetic and realistic snow images indicated that the proposed method achieves superior performance in respect of visual perception and objective evaluation.