• Proceedings of the IEEK Conference
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• 2000.11d
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• pp.17-20
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• 2000

This paper describes a shape-based object recognition algorithm using multiple distance images. For the images containing dense edge points and noise, previous Hausdorff distance (HD) measures yield a high ms error for object position and many false matchings for recognition. Extended version of HD measure considering edge position and orientation simultaneously is proposed for accurate matching. Multiple distance images are used to calculate proposed matching measure efficiently. Results are presented for visual images and infrared images.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2001.04a
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• pp.170-173
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• 2001

To apply stereo vision system to obstacle recognition system of AGV, we constructed algorithm of stereo matching and distance measuring with stereo image for positioning of object in area. And using this system, we look into the error between real position and measured position, and studied relationship of compensation.

• Proceedings of the KIEE Conference
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• 2002.11c
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• pp.542-545
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• 2002

Position transfer and turning rotation between fingerprint and inputted fingerprint that is registered in automatic fingerprint recognition system are one of main cause that mistaken acknowledgment expression happens. Therefore, in this research, conformity algorithm development that do it so that is unrelated in position translation and rotation of fingerprint at feature point conformity step to secure higher correct recognition rate.

• Journal of Korea Multimedia Society
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• v.14 no.5
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• pp.632-641
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• 2011

This paper presents a position error recognition system when the wafer is mounted in cleaning equipment among the wafer manufacturing processes. The proposed system is to enhance the performance in cost and reliability by preventing the wafer cleaning system from damaging by alerting it when it is put in correct position. The proposed algorithm is in obtaining a mapping function from camera and physical wafer by designing and manufacturing the radial shape calibrator to reduce the error by using the conventional chess board one. The system is to install in-line process using high reliable and high accurate position recognition. The experimental results show that the performance of the proposed system is better than that of the existing method for detecting errors within tolerance.

• KIPS Transactions on Software and Data Engineering
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• v.7 no.9
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• pp.345-350
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• 2018

This study is an algorithm for detecting vein pattern features important for finger vein recognition. The feature detection algorithm is important because it greatly affects recognition results in pattern recognition. The recognition rate is degraded because the reference is changed according to the finger position change. In addition, the image obtained by irradiating the finger with infrared light is difficult to separate the image background and the blood vessel pattern, and the detection time is increased because the image preprocessing process is performed. For this purpose, the presented algorithm can be performed without image preprocessing, and the detection time can be reduced. SWDA (Down Slope Trace Waveform) algorithm is applied to the finger vein images to detect the fingertip position and vein pattern. Because of the low infrared transmittance, relatively dark vein images can be detected with minimal detection error. In addition, the fingertip position can be used as a reference in the classification stage to compensate the decrease in the recognition rate. If we apply algorithms proposed to various recognition fields such as palm and wrist, it is expected that it will contribute to improvement of biometric feature detection accuracy and reduction of recognition performance time.

• Journal of Sasang Constitutional Medicine
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• v.18 no.3
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• pp.57-63
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• 2006

1. Objectives The Face is an important standard for the classification of Sasang Contitutions. Now We are developing 3D Face Automatic Recognition Apparatus to analyse the facial characteristics. This apparatus show us 3D image of man's face and measure facial figure. We should examine accuracy of position recognition in 3D Face Automatic Recognition Apparatus. 2. Methods We took a photograph of Face status with Land Mark 8 times using Face Automatic Recognition Apparatus. Each taking-photo, We span Face statusby 10 degree. At last time, We took a photograph of Face status's lateral face. And We analysed Error Averige of Distance between seven Land Marks. So We examined the accuracy of position recognition in 3D Face Automatic Recognition Apparatus at indirectly in degree changing of Face status. 3. Results and Conclusions According to degree change of Face status, Error Averige of Distance between Seven Land Marks is 0.1848mm. In conclusion, We assessed that accuracy of position recognition in 3D Face Automatic Recognition Apparatus is considerably good in spite of degree changing of Face status

• International Journal of Advanced Culture Technology
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• v.5 no.3
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• pp.67-72
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• 2017

Transform variation technique is constituted the vibration status of the flash-gap recognition level (FGRL) on the distribution recognition function. The recognition level condition by the distribution recognition function system is associated with the scattering vibration system. As to search a position of the dot model, we are consisted of the distribution value with character point by the output signal. The concept of recognition level is composed the reference of flash-gap level for variation signal by the distribution vibration function. For displaying a variation of the FGRL of the maximum-average in terms of the vibration function, and distribution position vibration that was the a distribution value of the far variation of the $Dis-rf-FA-{\alpha}_{MAX-AVG}$ with $5.74{\pm}1.12$ units, that was the a distribution value of the convenient variation of the $Dis-rf-CO-{\alpha}_{MAX-AVG}$ with $1.64{\pm}0.16$ units, that was the a distribution value of the flank variation of the $Dis-rf-FL-{\alpha}_{MAX-AVG}$ with $0.74{\pm}0.24$ units, that was the a distribution value of the vicinage variation of the $Dis-rf-VI-{\alpha}_{MAX-AVG}$ with $0.12{\pm}0.01$ units. The scattering vibration will be to evaluate at the ability of the vibration function with character point by the distribution recognition level on the FGRL that is showed the flash-gap function by the recognition level system. Scattering recognition system will be possible to control of a function by the special signal and to use a distribution data of scattering vibration level.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1920-1925
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• 2004

This paper describes a new method for 3D object recognition which used surface segment-based stereo vision. The position and orientation of an objects is identified accurately enabling a robot to pick up, even though the objects are multiple and partially occluded. The stereo vision is used to get the 3D information as 3D sensing, and CAD model with its post processing is used for building models. Matching is initially performed using the model and object features, and calculate roughly the object's position and orientation. Though the fine adjustment step, the accuracy of the position and orientation are improved.

• Transactions of the Korean Society of Mechanical Engineers
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• v.17 no.11
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• pp.2711-2722
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• 1993

Most of the current 2-D object recognition systems are model-based. In such systems, the representation of each of a known set of objects are precompiled and stored in a database of models. Later, they are used to recognize the image of an object in each instance. In this thesis, the approach method for the 2-D object recognition is treating an object boundary as a string of structral units and utilizing string matching to analyze the scenes. To reduce string matching time, models are rebuilt by means of fuzzy c-means clustering algorithm. In this experiments, the image of objects were taken at initial position of a robot from the CCD camera, and the models are consturcted by the proposed algorithm. After that the image of an unknown object is taken by the camera at a random position, and then the unknown object is identified by a comparison between the unknown object and models. Finally, the amount of translation and rotation of object from the initial position is computed.

• The Journal of Korea Robotics Society
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• v.15 no.1
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• pp.70-76
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• 2020

Multi-floor navigation of a mobile robot requires a technology that allows the robot to safely get on and off the elevator. Therefore, in this study, we propose a method of recognizing the elevator from the current position of the robot and estimating the location of the elevator locally so that the robot can safely get on the elevator regardless of the accumulated position error during autonomous navigation. The proposed method uses a deep learning-based image classifier to identify the elevator from the image information obtained from the RGB-D sensor and extract the boundary points between the elevator and the surrounding wall from the point cloud. This enables the robot to estimate the reliable position in real time and boarding direction for general elevators. Various experiments exhibit the effectiveness and accuracy of the proposed method.