• Journal of the Korean Institute of Telematics and Electronics B
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• v.30B no.4
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• pp.92-103
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• 1993

In this paper, we propose an adaptive classifier based on uncertainty of features for 3D planar object recognition. First, we investigate the uncertainty of depth information and the feature values of 3D planar object by numerical method. And, we observed that the statistical behavior of feature is dependent on the position and orientation of objects. After that, the approximation of the statistical behavior is executed. Subsequently, the recognition procedure is executed by the adaptive classifier. By computer simulation, we confirmed that the proposed classifier is useful for 3D planar object recognition.

• Proceedings of the Korea Information Processing Society Conference
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• 2006.11a
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• pp.19-22
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• 2006

In this paper we present a vision based place recognition method which uses Bayesian method with feed back of image retrieval. Both Bayesian method and image retrieval method are based on interest features that are invariant to many image transformations. The interest features are detected using Harris-Laplacian detector and then descriptors are generated from the image patches centered at the features' position in the same manner of SIFT. The Bayesian method contains two stages: learning and recognition. The image retrieval result is fed back to the Bayesian recognition to achieve robust and confidence. The experimental results show the effectiveness of our method.

• The Journal of Korea Robotics Society
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• v.5 no.2
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• pp.143-151
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• 2010

Automation and robotization has been required in construction for several decades and construction industry has become one of the important research areas in the field of service robotics. Especially in the steel construction, automatic recognition of structural steel members in the stockyard is emphasized. However, since the pose of steel frame in the stockyard is site dependent and also the stockyard is usually in the outdoor environment, it is difficult to determine the pose automatically. This paper adopts the recognition method based on the augmented reality to cope with this problem. Particularly focusing on the light condition of the outdoor environment, we formulated the optimization problem with the constraint and suggested the methodology to evaluate the optimal camera arrangement. From simulation results, sub-optimal solution for the position of the camera can be obtained.

• Proceedings of the KIEE Conference
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• 2004.05a
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• pp.102-104
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• 2004

Finger language is a typical tool for deaf persons. But learning the finger language for non-handicapped persons is very difficult. To overcome these difficulties, a new communication method using visual function is developed recently. Even though the developed system uses the visual function, it needs expensive equipments such as camera and computer. To be used in the real environments, the cost of equipments is a critical factor. If the recognition system for the finger language can be developed with low price equipments, the system can be used in the notebook or cellular phone. The image captured by PC camera was processed by preprocessing algorithm. To recognize the finger language, the resulting image was divide into $5{\times}5$ sections. The recognition system uses a similarity method and position information. The simulation results shows the effectiveness of the proposed algorithm.

• Journal of the Korean Society for Precision Engineering
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• v.8 no.1
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• pp.105-115
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• 1991

This paper describes an integrated CAD and CAPP system for prismatic parts of injection mold which generates a complete process plan automatically from CAD data of a part without human intervention. This system employs Auto CAD as a CAD model and GS-CAPP as an automatic process planning system for injection mold. The proposed CAD/CAPP system consists of three modules such as CAD data conversion module, manufacturing feature recognition module, and CAD/CAPP interface module. CAD data conversion module transforms design data of AutoCAD into three dimensional part data. Manufacturing feature recognition module extracts specific manufacturing features of a part using feature recognition rule base. Each feature can be recognized by combining geometry, position and size of the feature. CAD/CAPP interface module links manufacturing feature codes and other head data to automatic process planning system. The CAD/CAPP system can improve the efficiency of process planning activities and reduce the time required for process planning. This system can provide a basis for the development of part feature based design by analyzing manufacturing features.

• Journal of Auto-vehicle Safety Association
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• v.12 no.4
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• pp.23-30
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• 2020

Recently, self-driving research has been actively studied in various institutions. Accurate recognition is important because information about surrounding objects is needed for safe autonomous driving. This study mainly deals with the signal processing of LiDAR among sensors for object recognition. LiDAR is a sensor that is widely used for high recognition accuracy. First, we clustered and tracked objects by predicting relative position and speed of objects. The characteristic points of all objects were extracted using point cloud data of each objects through proposed algorithm. The Classification between vehicle and pedestrians is estimated using number of characteristic points and distances among characteristic points. The algorithm for classifying cars and pedestrians was implemented and verified using test vehicle equipped with LiDAR sensors. The accuracy of proposed object classification algorithm was about 97%. The classification accuracy was improved by about 13.5% compared with deep learning based algorithm.

• 제어로봇시스템학회:학술대회논문집
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• 1991.10a
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• pp.990-995
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• 1991

The integration of intelligent robots into manufacturing systems should positively impact the product quality and productivity. A new theory of object location and recognition using the supporting plane is presented. The unknown supporting points are determined by image coordinates, known camera parameters, and joint coordinates of the robot manipulators. This is developed by using the geometrical interpretation of perspective projection and the geometrical constraints of industrial environments. This can be applied to solve typical robot vision problems such as determination of position, orientation, and recognition of objects.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.161-161
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• 2000

The clean mobile robot for wafer transfer is AGV that carry each wafer to each equipment. It has wafer handling technology, wafer ID recognition technology, position calibration technology using vision system, and anti-vibration technology. Wafer loading/unloading working accuracy is within ${\pm}$1mm, ${\pm}$3$^{\circ}$. By application of this AGV, we can reduce the manufacturing tack time and bring cost down of equipment.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.28B no.11
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• pp.904-912
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• 1991

Automatic recognition of seal imprint has been required in the oriental countries. In this paper, a hierarchical approach for seal imprint verification is presented. Global features are used for seal imprint description in the first step. In the second step, conventional and several proposed local features are used to detect useful informations such as size, distribution and relative position of stroke length from seal imprint. In the last step, seal imprints are classified into one of three categories 'accept', 'ambiguous' and reject', based on the hierarchical classification. Experimental results show good performance on classification and recognition.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.32B no.9
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• pp.1154-1161
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• 1995

In this paper, a new method is proposed where the vision and ultrasonic sensor are used to recognize obstacles and to obtain its position and size. Ultrasonic snsors are used to obtain the actual navigation path width of the mobile robot. In conjunction with camera images of the path, recognition of obstacles and the determination of its distance, direction, and width are carried out. The characteristics of the sensors and the mobile robots used generally make it difficult to recognize all environments; accordingly, a restricted environment is employed for this study.