• Journal of Broadcast Engineering
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• v.10 no.2
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• pp.238-246
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• 2005

This paper proposes an iterative high-resolution image interpolation algorithm using spatially adaptive constraints and regularization functional. The proposed algorithm adapts adaptive constraints according to the direction of..edges in an image, and can restore high-resolution image by optimizing regularization functional at each iteration, which is suitable for edge directional regularization. The proposed algorithm outperforms the conventional adaptive interpolation methods as well as non-adaptive ones, which not only can restore high frequency components, but also effectively reduce undesirable effects such as noise. Finally, in order to evaluate the performance of the proposed algorithm, various experiments are performed so that the proposed algorithm can provide good results in the sense of subjective and objective views.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.31B no.11
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• pp.136-141
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• 1994

In this paper, we implemented an opto-electronical signal processing system for the edge detection using the diffusion neural network. The diffusion neural network performs a Gaussian and DOG operation efficiently by the diffusion process. The diffusion neural network is more efficient than the LOG masking method in hardware implementation because it has a few connections and the connection weights are fixed-valued. We implemented a diffusion neural network using the characteristics of the light intensity distribution function which is similar to the Gaussian function. We have shown that the system can detect the edge of an image exactly through the experimental results.

• Journal of the Korean Institute of Intelligent Systems
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• v.25 no.3
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• pp.260-265
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• 2015

This paper proposes a alignment system using edge feature. An alignment system obtains the position and orientation of printed circuit board(PCB) or liquid crystal display(LCD) panel through the fiducial marks. Thus, it is the indicator of the system performance how accurate we detect the positions of the fiducial marks in the target image. Edges have the geometrical characteristics such as positions, lengths, and shapes. These features are suitable for finding the marks and have the advantages of lighting variations, model occlusion, as well as variations in scale and angle. The performance of the proposed system is validated through the alignment experiment using an display panel alignment system included X, Y axis, and rotatable stage.

• Journal of Korea Multimedia Society
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• v.2 no.2
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• pp.129-136
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• 1999

A linear feature often provide sufficient information for image understanding and coding. An objective of the research reported in this paper is to develop and analyze the reliable methods of extracting lines in gray scale images. The Hough Transform is known as one of the optimal paradigms to detect or identify the linear features by transforming edges in images into peaks in parameter space. The scheme proposed here uses the fuzzy gradient direction model and weights the gradient magnitudes for deciding the voting values to be accumulated in parameter space. This leads to significant computational savings by restricting the transform to within some support region of the observed gradient direction which can be considered as a fuzzy variable and produces robust results.

• Journal of KIISE:Software and Applications
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• v.36 no.11
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• pp.912-919
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• 2009

A novel algorithm using 2D tensor voting and edge-based approach is proposed for text detection in natural scene images. The tensor voting is used based on the fact that characters in a text line are usually close together on a smooth curve and therefore the tokens corresponding to centers of these characters have high curve saliency values. First, a suitable edge-based method is used to find all possible text regions. Since the false positive rate of text detection result generated from the edge-based method is high, 2D tensor voting is applied to remove false positives and find only text regions. The experimental results show that our method successfully detects text regions in many complex natural scene images.

• Journal of Korea Multimedia Society
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• v.13 no.11
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• pp.1610-1620
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• 2010

This paper proposes a motion-adaptive 3-D deinterlacing algorithm based on an adaptive-thresholded motion detection and an interpolation method using binary patterns to compensate motion missing and false motion errors. For efficient motion detection, we adaptively decided a threshold value according to the complexity of image. Many edge-based interpolation algorithms have been proposed to improve the subjective quality. Recently, to efficiently interpolate low angle edge and line, a method using predefined binary patterns has been proposed. In this paper, we propose an improved method by modifying the binary patterns. Simulation results have shown that the proposed method provides better performance than the existing methods.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.9 no.7
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• pp.1594-1600
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• 2005

Recently many researches have been studied in the human vision model to solve the Wblem of the machine vision. Starting from research on the human visual system, first, we investigate the mechanisms of retina through physiological and biological evidence. In retina, input data was processed information processing that was data reduction edge detection, and emphasizing region. The processed image was recognized by region. In this paper, we proposed retinal algorithms that process data reduction and edge detection by the wavelet transform and emphasize region contrast. In experiments, the proposed model simulates processing the retina outputs in the levels and compares with outputs.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.4 no.2
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• pp.155-160
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• 2004

In this paper, we describe the results of a study on the edge enhancement of X-ray images by using their fuzzy system representation. A set of gray scale X-ray images was generated using the EGS4 computer code. An aluminum plate or a lead plate with three parallel strips taken out has been used as the object with the thickness and the width of the plate, and the gap between the two strips varied. We started with a comparative study on a set of the fuzzy sets for their applicability as the input fuzzy sets for the fuzzy system representation of the gray scale images. Then we describe how the fuzzy system is used to sharpen the edges. Our algorithm is based on adding the magnitude of the gradient not to the pixel value of concern but rather to the nearest neighboring pixel in the direction of the gradient. We show that this algorithm is better in maintaining the spatial resolution of the original image after the edge enhancement.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.9
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• pp.2312-2325
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• 2013

In this paper, we propose a preprocessing method that it is to correct the distortion of text area in Korean signboard images as a preprocessing step to improve character recognition. Distorted perspective in recognizing of Korean signboard text may cause of the low recognition rate. The proposed method consists of four main steps and eight sub-steps: main step consists of potential vertical components detection, vertical components detection, text-boundary estimation and distortion correction. First, potential vertical line components detection consists of four steps, including edge detection for each connected component, pixel distance normalization in the edge, dominant-point detection in the edge and removal of horizontal components. Second, vertical line components detection is composed of removal of diagonal components and extraction of vertical line components. Third, the outline estimation step is composed of the left and right boundary line detection. Finally, distortion of the text image is corrected by bilinear transformation based on the estimated outline. We compared the changes in recognition rates of OCR before and after applying the proposed algorithm. The recognition rate of the distortion corrected signboard images is 29.63% and 21.9% higher at the character and the text unit than those of the original images.

• Journal of Astronomy and Space Sciences
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• v.29 no.2
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• pp.199-208
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• 2012

The world's first geostationary ocean color imager (GOCI) is a three-mirror anastigmat optical system 140 mm in diameter. Designed for 500 m ground sampling distance, this paper deals with on-orbit modulation transfer function (MTF)measurement and analysis for GOCI. First, the knife-edge and point source methods were applied to the 8th band (865 nm) image measured April 5th, 2011. The target details used are the coastlines of the Korean peninsula and of Japan, and an island 400 meters in diameter. The resulting MTFs are 0.35 and 0.34 for the Korean East Coastline and Japanese West Coastline edge targets, respectively, and 0.38 for the island target. The daily and seasonal MTF variations at the Nyquist frequency were also checked, and the result is $0.32{\pm}0.04$ on average. From these results, we confirm that the GOCI on-orbit MTF performance satisfies the design requirements of 0.32 for 865 nm wavelength.