• Journal of the Korean Institute of Electrical and Electronic Material Engineers
• /
• v.19 no.2
• /
• pp.185-188
• /
• 2006

We studied on the reverse twist near the pixel edge depending on the rubbing direction for the fringe field switching (FFS) mode. Liquid crystal (LC) dynamic and the transmittance near the pixel edge, where the various field directions are generated, depend on the initial rubbing direction because the position of reverse twist is decided by the angle between the electric direction and the LC director at a bias voltage. For example, when the rubbing angle is $7^{\circ}$, the reverse twist appears on the bottom position of the right sharp comer of the pixel edge so that the reverse region exists far away from main active region. But, when the rubbing angle is $-7^{\circ}$, the reverse twist appears on the top position of the right sharp comer of the pixel edge, resulting that the region becomes more close to the main active area and the unstable disclination lines (DLs) easily intrude into the active region. Therefore, it is necessary to keep the reverse twist region far from the active region and it is possible by controlling the rubbing direction in the design of a pixel electrode.

• Journal of Information Processing Systems
• /
• v.16 no.1
• /
• pp.49-60
• /
• 2020

To solve the edge ringing or block effect caused by the partial differential diffusion in image enhancement domain, a new image enhancement algorithm based on bidirectional diffusion, which smooths the flat region or isolated noise region and sharpens the edge region in different types of defect images on aviation composites, is presented. Taking the image pixel's neighborhood intensity and spatial characteristics as the attribute descriptor, the presented bidirectional diffusion model adaptively chooses different diffusion criteria in different defect image regions, which are elaborated are as follows. The forward diffusion is adopted to denoise along the pixel's gradient direction and edge direction in the pixel's smoothing area while the backward diffusion is used to sharpen along the pixel's gradient direction and the forward diffusion is used to smooth along the pixel's edge direction in the pixel's edge region. The comparison experiments were implemented in the delamination, inclusion, channel, shrinkage, blowhole and crack defect images, and the comparison results indicate that our algorithm not only preserves the image feature better but also improves the image contrast more obviously.

• 제어로봇시스템학회:학술대회논문집
• /
• 2005.06a
• /
• pp.2389-2392
• /
• 2005

We present fast stereo matching algorithm using edge projection. Traditional stereo matching algorithm uses 2D template for the search of corresponding point thus it requires huge the computational cost. In this paper, we reduce the 2D search problem into 1D using edge projection along vertical and horizontal direction inside the region of interest. Also, by accumulation of edge projection along vertical and horizontal direction, the edge projection within the region of interest could simply be obtained by just subtracting two values. Experimental results show that matching algorithm using edge projection also gives comparable discriminating power compared to that of using intensity.

• Journal of the Institute of Electronics Engineers of Korea SP
• /
• v.47 no.1
• /
• pp.53-61
• /
• 2010

In this paper, we present a color interpolation algorithm that uses novel edge direction estimator and region classifier. The proposed edge direction estimator accurately determines the edge direction based on the correlation between the images obtained by the channel separated and down-sampled Bayer color filter array(CFA) pattern. The correlation is defined based on the similarity between the edge direction in the local region of the image and the shifting direction of the images. Also, the region of an image is defined as the flat, the edge, and the pattern-edge regions, where the edges are appeared repeatedly. When all the pixels in the image are classified into the three different regions, each pixel is interpolated horizontally or vertically according to the estimated direction. Experimental results show that the proposed algorithm outperforms the conventional edge-directed methods on objective and subjective criteria.

• International journal of advanced smart convergence
• /
• v.11 no.4
• /
• pp.47-56
• /
• 2022

Recently bank card number recognition plays an important role in improving payment efficiency. In this paper we propose a new bank-card number identification algorithm. The proposed algorithm consists of three modules which include edge detection, candidate region generation, and recognition. The module of 'edge detection' is used to obtain the possible digital region. The module of 'candidate region generation' has the role to expand the length of the digital region to obtain the candidate card number regions, i.e. to obtain the final bank card number location. And the module of 'recognition' has Convolutional deep learning Neural Network (CNN) to identify the final bank card numbers. Experimental results show that the identification rate of the proposed algorithm is 95% for the card numbers, which shows 20% better than that of conventional algorithm or method.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.64 no.9
• /
• pp.1369-1373
• /
• 2015

Curve subdivision interpolation reconstructs edge well with low complexity, however it lacks of ability to recover texture components, instead. While, neighbor embedding is superior in texture reconstruction. Therefore, in this paper, a novel Super Resolution technique which combines curve subdivision interpolation and neighbor embedding is proposed. First, edge region and non-edge regions are classified. Then, for edge region, the curve subdivision algorithm is used to make two polynomials derived from discrete pixels and adaptive weights are adapted for gradients of 4 different sides to make smooth edge. For non edge region, neighbor-embedding method is used to conserve texture property in original image. Consequently results show that the proposed technique conserves sharp edges and details in texture better, simultaneously.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.17 no.3
• /
• pp.718-723
• /
• 2013

In general, the boundary portion of the background and objects are the rapidly changing point and an important elements to analyze characteristics of image. Using these boundary parts, information about the position or shape of an object in the image are detected, and many studies have been continued in order to detect it. Existing methods are that implementation of algorithm is comparatively simple and its processing speed is fast, but edge detection characteristics is insufficient because weighted values are applied to all the pixels equally. Therefore, in this paper, we proposed an algorithm using region segmentation of the mask in order to adaptive edge detection according to image, and the results processed by proposed algorithm indicated superior edge detection characteristics in edge area.

• Journal of the Korean Institute of Telematics and Electronics B
• /
• v.29B no.11
• /
• pp.111-119
• /
• 1992

In this paper, we propose an edge detection scheme for noisy images based on the co-occurrence matrix. In the proposed scheme based on the step edge model, the gray level information is simply converted into a bit-map, i.e., the uniform and boundary regions of an image are transformed into a binary pattern by using the local mean. In this binary bit-map pattern, 0 and 1 densely distributed near the boundary region while they are randomly distributed in the uniform region. To detect the boundary region, the co-occurrence matrix on the bit-map is introduced. The effectiveness of the proposed scheme is shown via a quantitative performance comparison to the conventional edge detection methods and the simulation results for noisy images are also presented.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.59 no.8
• /
• pp.1477-1481
• /
• 2010

In this paper, we propose the classification and tracking method of the hand region using deformable template and condensation. To do this, first, we extract the hand region by using the fuzzy color filter and HCbCr color model. Second, we extract the edge of hand by applying the Canny edge algorithm. Third, we find the first template by calculating the conditional probability between the extracted edge and the model edge. If the accurate template of the first object is decided, the condensation algorithm tries to track it. Finally, we demonstrate the effectiveness and feasibility of the proposed method through some experiments.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.38C no.9
• /
• pp.757-763
• /
• 2013

This study discusses the multiple knife-edge diffraction loss with the receiver and jammer located in the Seoul metropolitan northwestern region. The considered positioning and jamming signals are the GPS L1 C/A signal and several jamming signals such as the wideband Gaussian noise, matched spectrum, and continuous wave signals. To calculate the accurate diffraction effects, the 3-dimensional topography data at the Seoul metropolitan northwestern region was used.