• Archives of design research
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• v.15 no.1
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• pp.359-368
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• 2002

Fabric art is most distinguished field among the Modern art. Among them, tapestry which begins human history is investigated more and more deeply and till now it displays with various type and exhibition. But, because of the huge scale of the working process, it requires much time and hard endeavor. After sampling, it begins main process in the present situation. But we cannot know exactly whether it goes well or not until it ends. So after fulfilled whole process, we often try new work again. Because of this reason, we devise computer simulation. With computer simulation we can preview whole working and lengthen the planning time, shorten the needless time. Simulation is made up of Scan, Drawing, Line clean up, Rendering, Parity, and Printing. Scan and Drawing can male new idea. And during the Line clean up we can make vector image and modify the image. And then rendering the image and inquiring the length and weight of yarn. Last process is printing an then making a package soft ware by means of prototype. Through these process, many producers and student can easily access to tapestry and reduce the needless time and endeavor.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.9
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• pp.1681-1688
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• 2017

In this paper, we implemented a high-speed signal processing hardware system for Color Line Scan Camera using FPGA and Nor-Flash. The existing hardware system mainly processed by high-speed DSP based on software and it was a method of detecting defects mainly by RGB individual logic, however we suggested defect detection hardware using RGB-HSL hardware converter, FIFO, HSL Full-Color Defect Decoder and Image Frame Buffer. The defect detection hardware is composed of hardware look-up table in converting RGB to HSL and 4K HSL Full-Color Defect Decoder with high resolution. In addition, we included an image frame for comprehensive image processing based on two dimensional image by line data accumulation instead of local image processing based on line data. As a result, we can apply the implemented system to the grain sorting machine for the sorting of peanuts effectively.

• Proceedings of the Korean Statistical Society Conference
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• 2002.05a
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• pp.119-125
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• 2002

우리는 본 논문에서 디지털 영상에 대하여 Hash함수를 이용한 내용기반의 안전한 워터마킹 인증기술을 제시하려고 한다. 허가되지 않는 이미지의 내용변경을 막기 위해 안전한 워터마킹 시스템을 개발하기 위하여 비밀키를 가지고 있는 Hash 함수가 사용되었고, 각 블록의 워터마크신호는 Hash함수의 출력결과를 Seed로 사용하여 의사난수를 발생시킨 값에 따라 생성되어진다. 이미지 기술벡터들은 블록기반 에지 이미지로부터 측정되는데 이 값들은 해롭지 않는 조작 등에 대해서는 쉽게 변화하지 않지만 고의적인 내용변경 등의 조작에 대해서는 이들 값들이 바꾸어지는 성질을 갖고 있다. 워터마크신호의 삽입은 블록기반 스펙트럼 방법에 기초를 두고 있으며 워터마크신호의 크기는 인지성과 강인성이 조화를 이루도록 AC 부 밴드의 지그재그 스캔라인의 DCT 계수들의 지역적인 통계량에 따라 조정되어진다. 또한 저작권인증의 확인을 위한 경계 값의 선택은 통계학적으로 분석되어진다. 수치적인 실험의 결과는 제안된 기술이 강력한 저작권인증의 수행을 위해서 매우 효율적인 것을 보여주고 있다.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.21 no.10
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• pp.1551-1560
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• 1997

This study is devoted to the detection of the 3-dimensional point obstacles on the plane by using accumulated scan line images. The proposed accumulating only one scan line allow to process image at real time. And the change of motion of the feature in image is small because of the short time between image frames, so it does not take much time to track features. To obtain recursive optimal obstacles position and robot motion along to the motion of camera, Kalman filter algorithm is used. After using Kalman filter in case of the fixed environment, 3-dimensional obstacles point map is obtained. The position and motion of moving obstacles can also be obtained by pre-segmentation. Finally, to solve the stereo ambiguity problem from multiple matches, the camera motion is actively used to discard mis-matched features. To get relative distance of obstacles from camera, parallel stereo camera setup is used. In order to evaluate the proposed algorithm, experiments are carried out by a small test vehicle.

• Journal of the Korean Society of Visualization
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• v.6 no.2
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• pp.20-27
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• 2008

The color sorting technique utilizing the image processing method is very applicable tool to analyze motion of a free-falling object in many agricultural and industrial research fields. In the present study, we have developed an image processing system and algorithm to sort good quality rice grains effectively from the bad ones. The system employs a high speed rate line-scan CCD camera with 2K-pixels and worked with a high speed DSP and FPGA in-line. It can accumulate acquired line-scan image data and visualize each grain image clearly. As a result, we can easily calculate the number of pixels occupied by grain(=grain size), gray level and its correct position by visualizing grain images rapidly.

• Journal of Digital Convergence
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• v.16 no.3
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• pp.303-309
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• 2018

Computer vision technology is a component inspection to obtain a video image from the camera to the machine to perform the capabilities of the human eye with a field of artificial intelligence, and then analyzed by the algorithm to determine to determine the good and bad of production parts It is widely applied. Shape inspection method was used as how to identify the location of the start point and the end point of the search range, measure the height to the line scan method, in such a manner as to determine the presence or absence of the bolt tabs average brightness of the inspection area in a circular scan type value And the degree of similarity was calculated. The total time it takes to test in the test performance tests of two types of bolts tab enables test 300 min, and demonstrated the accuracy and efficiency of the inspection on the production line represented a complete inspection accuracy.

• Journal of KIISE:Computer Systems and Theory
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• v.31 no.3_4
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• pp.187-194
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• 2004

Shear-Warp volume rendering has many advantages such as good image Quality and fast rendering speed. However in the interactive classification environment it has low efficiency of memory access since preprocessed classification is unavailable. In this paper we present an algorithm using the spacial locality of memory access in the interactive classification environment. We propose an extension model appending a rotation matrix to the factorization of viewing transformation, it thus performs a scanline-based rendering in the object and image space. We also show causes and solutions of three problems of the proposed algorithm such as inaccurate front-to-back composition, existence of hole, increasing computational cost. This model is efficient due to the spacial locality of memory access.

• Journal of Korea Society of Industrial Information Systems
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• v.23 no.1
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• pp.13-21
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• 2018

AGVS (Automated Guided Vehicle System) is a core technology of logistics automation which automatically moves specific objects or goods within a certain work space. Conventional AGVS generally requires the in-door localization system and each AGV equips expensive sensors such as laser, magnetic, inertial sensors for the route recognition and automatic navigation. thus the high installation cost is inevitable and there are many restrictions on route(path) modification or expansion. To address this issue, in this paper, we propose a cost-effective and scalable AGV based on a light-weight pattern recognition technique. The proposed pattern recognition technology not only enables autonomous driving by recognizing the route(path), but also provides a technique for figuring out the loc ation of AGV itself by recognizing the simple patterns(bar-code like) installed on the route. This significantly reduces the cost of implementing AGVS as well as benefiting from route modification and expansion. In order to verify the effectiveness of the proposed technique, we first implement a pattern recognition algorithm on a light-weight MCU(Micro Control Unit), and then verify the results by implementing an MCU_controlled AGV prototype.

• The KIPS Transactions:PartD
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• v.9D no.5
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• pp.915-924
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• 2002

Conventional Systems for parcel sorting consist of two sequences as loading the parcel into conveyor belt system and post-code input. Using bar code information, the parcels to be recorded and managed are recognized. This paper describes a 32 $\times$ 32 sized mini-block inspection to extract bar code Region of Interest (ROI) from the line Charged Coupled Device (CCD) camera capturing image of moving parcel at 2m/sec speed. Firstly, the Min-Max distribution of the mini-block has been applied to discard the background of parcel and region of conveying belts from the image. Secondly, the diagonal inspection has been used for the extraction of letters and bar code region. Five horizontal line scanning detects the number of edges and sizes and ROI has been acquired from the detection. The wrong detected area has been deleted by the comparison of group size from labeling processes. To correct excluded bar code region in mini-block processes and for analysis of bar code information, the extracted ROI 8 boundary points and decline distribution have been used with central axis line adjustment. The ROI extraction and central axis creation have become enable within 60～80msec, and the accuracy has been accomplished over 99.44 percentage.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.4
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• pp.793-799
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• 2007

Generally, a semiconductor chip measured with a few micro units is captured by line scan camera for higher inspection accuracy. However, the faulty inspection requires an exact boundary detection algorithm, because it is very sensitive to scan speed and lighting conditions. In this paper we propose boundary detection with subpixel edge detection in order to increase the accuracy of bump faulty detection on chips. The bump edge is detected by first derivative to four directions from bump center point and the exact edge positions are searched by the subpixel method. Also, the exact bump boundary to calculate the actual bump size is computed by LSM(Least Squares Method) to minimize errors since the bump size is varied such as bump protrusion, bump bridge, and bump discoloration. Experimental results exhibit that the proposed algorithm shows large improvement comparable to the other conventional boundary detection algorithms.