• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.379-382
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• 1997

This paper introduces a new vision technique for extracting roof edges of polyhedra having specularly reflecting surfaces. There have been many previous works on object recognition using edge information. But they can not be applied to specular objects since it is hard to acquire reliable camera images of specular objects. If there is a method which can extract the edges of specular objects, it is possible to apply edge-based recognition algorithms to specular objects. To acquire the reliable edge images of specular objects, scanned double pass retroreflection method is proposed, whose main physical characteristic is curvature-sensitive. This utility of the physical characteristic is motivated by the idea that roof edges can be characterized as local surfaces of high curvature. In this paper, the optical characteristics of double pass retroreflection are discussed and a series of simulation studies are performed to verify and analyze the sensor characteristics. The results from a series of simulations show the effectiveness of the proposed method.

• Journal of Contemporary Eastern Asia
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• v.13 no.1
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• pp.39-55
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• 2014

This study aims to examine and develop a Triple Helix model for social innovation to eradicate pervasive poverty in developing countries. To do this, this study explores and analyzes the Rural Saemaul Undong (RSU), a rural community development movement for eradicating poverty that was driven by the South Korean government during the 1970s. First of all, this study explores the characteristics of the RSU and explains why the RSU was a social innovation. To support and explain why the RSU was a successful social innovation, this study analyzes the roles and activities of three distinct actor groups: the chief policymaker and his aides who presented the vision and purpose, or the "why" of the Saemaul Undong; central and local government officials who were the planners and managers who showed "how" to plan and drive it; and village Saemaul leaders as the drivers and coaches showing rural villagers "what" to do. Based on this analysis, this study develops an actor-based Triple Helix model for social innovation to eradicate poverty.

• Journal of the Korea Society of Computer and Information
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• v.6 no.1
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• pp.31-37
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• 2001

Human psychovisual phenomena involved in extracting features is more sensitive in dark regions than in bright regions Therefore, feature extracting operators should be considered local intensities in order to perceive objects analogous to human vision system. Generally, conventional feature extracting operators have some handicaps like an computational complexity or multivariable needs. In this paper a novel feature extracting operator is proposed to overcome these demerits. This operator could be implemented very simply and be proved good performances through experiments applied to synthetic and real images.

• Proceedings of the KIEE Conference
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• 1990.11a
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• pp.460-464
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• 1990

Texture provides an important source of information about the local orientation of visible surfaces. An important task that arises in many computer vision systems is the reconstruction of three-dimensional depth information from two-dimensional images. The surface orientation of texel is classified by the Artificial Neural Network. The classification method to recognize the shape of 3D object with artificial neural network requires less developing time comparing to conventional method. The segmentation problem is assumed to be solved. The surface in view is smooth and is covered with repeated texture elements. In this study, 3D shape reconstruct using interpolation method.

• 제어로봇시스템학회:학술대회논문집
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• 1991.10b
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• pp.1748-1751
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• 1991

Generally, we can't acquire clear boundary or area from an image having obscure boundary like allergy image by using Sobel or Lapalace operator. Also, when the image not uniform in some part of a image in brightness, there are difficulties to use the global operator such as histogram, for the contour line doesn't have the same grey level. In this paper, we will propose an algorithm to improve those difficulties. The main idea of the algorithm is that we divide the image into many rectangular parts like a chess board, calculate the average of each part, and decide the local threshold for each pixel on the calculated value. In experiment, we can get the contour and area by this algorithm which is much like to the contour and area measured by a doctor. Also, This algorithm has many advantages such as short processing time and little influences of noises and can be used in the robot vision, etc..

• Journal of the Korean Institute of Telematics and Electronics B
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• v.33B no.4
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• pp.101-110
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• 1996

Color image quantization is a process of selecting a set of colors to display an image with some representative colors without noticeable perceived difference. It is very important in many applications to display a true color image in a low cost color monitor or printer. the basic problem is how to display 224 colors with 256 or less colors, called color palette. In this paper, we propose an algorithm to design the 256 or less size color palette by using spatial maskin geffect of HVS and subjective distortion measure weighted by color palette by using spatial masking effect of HVS and subjective distortion measure weighted by color activity in 4*4 local region in any color image. The proposed algorithm consists of octal prequantization and subdivision quantization processing step using the distortion measure and modified Otsu's between class variance maximization method. The experimental results show that the proposed algorithm has higher visual quality and needs less consuming time than conventional algorithms.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.644-647
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• 2003

This paper describes a neural network based machine vision system designed for inspecting yellow beans in real time. The system consists of a camera. lights, a belt conveyor, air ejectors, and a computer. Beans are conveyed in four lines on a belt and their images are taken by a monochrome line scan camera when they fall down from the belt. Beans are separated easily from their background on images by back-lighting. After analyzing the image, a decision is made by a multilayer artificial neural network (ANN) trained by the error back-propagation (EBP) algorithm. We use the global mean, variance and local change of gray levels of a bean for the input nodes of the network. In an our experiment, the system designed could process about 520kg/hour.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.5 no.2
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• pp.57-62
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• 1996

Basically, the idea underlying most edge-detection technique is the computation of a local derivative operator used for edge detection in gray level image. This concept can be easily illustrated with the aid of object which shows an image of a simple lilght on a dark background, Using the gray level profile along a horizontal scan line of the image. the first and second derivatives of it were acquired. This study is to develop an automatic measuring system based on the digital image processing which can be applied to the real time measurement of the characteristics of the ultra-thin thickness. The experimental results indicate that the developed automatic inspection can be applied in real situation.

• Journal of Information Processing Systems
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• v.13 no.2
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• pp.256-267
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• 2017

An active research area in computer vision, stereo matching is aimed at obtaining three-dimensional (3D) information from a stereo image pair captured by a stereo camera. To extract accurate 3D information, a number of studies have examined stereo matching algorithms that employ adaptive support weight. Among them, the adaptive census transform (ACT) algorithm has yielded a relatively strong matching capability. The drawbacks of the ACT, however, are that it produces low matching accuracy at the border of an object and is vulnerable to noise. To mitigate these drawbacks, this paper proposes and analyzes the features of an improved stereo matching algorithm that not only enhances matching accuracy but also is also robust to noise. The proposed algorithm, based on the ACT, adopts the truncated absolute difference and the multiple sparse windows method. The experimental results show that compared to the ACT, the proposed algorithm reduces the average error rate of depth maps on Middlebury dataset images by as much as 2% and that is has a strong robustness to noise.

• Journal of Korea Multimedia Society
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• v.19 no.6
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• pp.1014-1023
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• 2016

In this study, we presented a method for non-square Differential LBP operation that can well describe the micro pattern in the horizontal and vertical component. We proposed a way to represent a LBP operation with various direction components as well as the diagonal component. In order to verify the validity of the proposed operation, Differential LBP was investigated with respect to accuracy, sensitivity, and specificity for the classification of facial expression. In accuracy comparison proposed LBP operation obtains better results than Square LBP and LBP-CS operations. Also, Proposed Differential LBP gets better results than previous two methods in the sensitivity and specificity indicators 'Neutral', 'Happiness', 'Surprise', and 'Anger' and excellence Differential LBP was confirmed.