• The Journal of Korean Institute of Communications and Information Sciences
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• v.17 no.1
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• pp.80-89
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• 1992

This paper presents algorithms which are region labeling and data structure of a boundary segmentation as image intermediate description process. In the method, the algorithms are region labeling, boundary segmentation, line and curve fitting and extracting data structure of each segment. As a result, a data structure of image is described by a set of region number, segment number, line or curve, starting point and end point of each segment and coefficient of line or curve. These data structures would serve for higher level processing as object recognition. For example we will use this data structure to solve the correspondence problem of stereoscopic image information. And we verified these algorithms through the image reconstruction of data structure.

• Journal of the Korea Society of Computer and Information
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• v.13 no.6
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• pp.243-251
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• 2008

This study is to suggest the extraction algorithms of fingerprint corepoint and region separation using the labeling for gate security in order that it might be applied to the fingerprint recognition effectively. The gate security technology is entrance control, attendance management, computer security, electronic commerce authentication, information protection and so on. This study is to extract the directional image by dividing the original image in $128{\times}128$ size into the size of $4{\times}4$ pixel. This study is to separate the region of directional smoothing image extracted by each directional by using the labeling, and extract the block that appeared more than three sorts of change in different directions to the corepoint. This researcher is to increase the recognition rate and matching rate by extracting the corepoint through the separation of region by direction using the maximum direction and labeling, not search the zone of feasibility of corepoint or candidate region of corepoint used in the existing method. According to the result of experimenting with 300 fingerprints, the poincare index method is 94.05%, the proposed method is 97.11%.

• Journal of Digital Convergence
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• v.11 no.4
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• pp.259-266
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• 2013

Binary connected-components labeling, which is widely used in the field of the pattern recognition, has been researched for a long time as one of the basic image processing techniques. Two-scan algorithm has been mainly used in the researches of the connected-components labeling. Recently, for the first scan in the two-scan algorithm, block-based labeling approaches have been used and reported as the fastest methods. In this paper, a new efficient scan mask for connected-components labeling with a block-based labeling approach is proposed. Labeling with the new pixel-based scan mask is more efficient than any other existing method. The results of the experiments show that the proposed method is faster than the existing fastest method.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10a
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• pp.442-445
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• 1996

This paper proposes a technique for analyzing mutual relation of an entangled cord by consistent labeling. Cords are often entangled unexpectedly and sometimes they even produce knots. The purpose of this study is to provide an algorithm to resolve such entangled cords automatically. It may as well have applications in future to recognizing the structure of tree branches, angiography, abdominal intestines, etc.

• Journal of KIISE:Software and Applications
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• v.31 no.7
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• pp.922-928
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• 2004

We propose a new 3 dimensional labeling method based on slice information for the volume data. This method is named SIL (Slice Information based Labeling). Compare to the conventional algorithms, it has advantages that the use of memory is efficient and it Is possible to combine with a variety of 2 dimensional labeling algorithms for finding an appropriate labeling algorithm to its application. In this study, we applied SIL to confocal microscopy images of cervix cancer cell and compared the results of labeling. According to the measurement, we found that the speed of Sd combined with, CCCL (Contour based Connected Component Labeling) is almost 2 times higher than that of other methods. In conclusion, considering that the performance of labeling depends on a kind of image, we obtained that the proposed method provide better result for the confocal microscopy cell volume data.

• Journal of Drive and Control
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• v.20 no.4
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• pp.92-99
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• 2023

Autonomous vehicles should recognize and respond to the specified speed to drive in compliance with regulations. To recognize the specified speed, the most representative method is to read the numbers of the signs by recognizing the speed signs in the front camera image. This study proposes a method that utilizes YOLO-Labeling-Labeling-EfficientNet. The sign box is first recognized with YOLO, and the numeric digit is extracted according to the pixel value from the recognized box through two labeling stages. After that, the number of each digit is recognized using EfficientNet (CNN) learned with the virtual environment dataset produced directly. In addition, we estimated the depth of information from the height value of the recognized sign through regression analysis. We verified the proposed algorithm using the virtual racing environment and GTSRB, and proved its real-time performance and efficient recognition performance.

• Proceedings of the KIEE Conference
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• 2004.11c
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• pp.184-186
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• 2004

This paper is about vision system that exhibits automatic examination of the conditions of shaft's worm. The system is composed of three part : image acquisition, vision algorithm, and user interface. The image acquisition part is composed of motor control, illumination and optics. The vision algorithm examines the parts by labeling algorithm using shaft image. User interface is divided into two parts, user interface for feature registering with control value settings and user interface for examination operation. The automatic inspection system of this research is a tool for final examination of shaft worm. This tool can be practically used in production lines with simple adjustments.

• Journal of Industrial Technology
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• v.30 no.A
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• pp.25-29
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• 2010

In this paper, we implement a multi-touch system using FIDR. The implementation consists of hardware manufacture and development of image processing system. In the hardware system, touch screen, infrared LED placements and infrared camera are made. The image processing procedure is to extract each pointer's coordinates from image data and includes binary-coding, noise-elimination, labeling and calculation of mass center. From the implementation, we are able to make a multi-touch system with considerably lower cost than the existing ones.

• Proceedings of the KIEE Conference
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• 2001.07d
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• pp.2738-2740
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• 2001

This paper describes a study on implementation of image processing systems for the defect inspection of polyethylene. In order to detect the edge, the Robert filter is used. And we use to the labeling algorithm for feature extraction. Labeling the conected regions of a image is a fundamental computation in image analysis and machine vision, with a large number of application. This algorithm is designed for the defect inspection of polyethylene.

• Journal of Institute of Control, Robotics and Systems
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• v.3 no.5
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• pp.497-502
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• 1997

In this study an automatic rolling-coil labeling system using robot vision system and peripheral mechanism is proposed and implemented, which instead of the manual labor to attach labels Rolling-coils in a steel mill. The binary image process for the image processing is performed with the threshold, and the contour line is converted to the binary gradient which detects the discontinuous variation of brightness of rolling-coils. The moments invariant algorithm proposed by Hu is used to make it easy to recognize even when the position of the center are different from the trained data. The position error compensation algorithm of six degrees of freedom industrial robot manipulator is also developed and the data of the position of the center rolling-coils, which is obtained by floor mount camera, are transferred by asynchronous communication method. Therefore, even if the position of center is changed, robot moves to the position of center and performs the labeling work successfully. Therefore, this system can be improved the safety and efficiency.