• Journal of Power System Engineering
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• v.11 no.4
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• pp.103-108
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• 2007

In general, the swing motion of the crane is controlled and suppressed by activating the trolley motion. In many papers reported by us, we suggested a new type of anti-sway control system of the crane. In the proposed control system, a small auxiliary mass(moving-mass) is installed on the spreader and the swing motion is controlled by moving the auxiliary mass. The actuator reaction against the auxiliary mass applies inertial control forces to the container in order to reduce the swing motion in the desired manner. The measuring system is based on laser sensor or others. However it is not so useful in real world. Especially, in this paper, the image sensor is used to measures the motions of the spreader and the measured data are fed back to the controller in real time. The applied image processing technique is a kind of robust template matching method which is named Vector Code Correlation (VCC) and devised to consider the real environmental conditions. And the $H_{\infty}$ based control technique is applied to suppress swing motion of the crane. And the experimental result shows that the proposed measurement system based on image sensor and control system is useful and robust to disturbances.

• Journal of Biomedical Engineering Research
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• v.20 no.4
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• pp.419-425
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• 1999

In this paper, we present an algorithm of real time facial expression and gesture recognition for image sequence on the gray level. A mixture algorithm of a template matching and knowledge based geometrical consideration of a face were adapted to locate the face area in input image. And optical flow method applied on the area to recognize facial expressions. Also, we suggest hand area detection algorithm form a background image by analyzing entropy in an image. With modified hand area detection algorithm, it was possible to recognize hand gestures from it. As a results, the experiments showed that the suggested algorithm was good at recognizing one's facial expression and hand gesture by detecting a dominant motion area on images without getting any limits from the background image.

• Journal of Power System Engineering
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• v.17 no.5
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• pp.121-127
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• 2013

In this paper, we propose a distance measurement system for automatic berthing control using a stereo camera mounted on a rotation control device, and a radial pattern target. Automatically controlling the position and attitude of a ship aims to prevent maritime accidents due to human error. Our goal is to measure the relative distance between a ship and an onshore or offshore target for berthing. Therefore, the distance should be continuously measured while tracking a fixed point on a target. To this end, we developed a stereo camerabased distance measurement system that satisfied these requirements. This paper describes the structure and principle of the measurement system. We validate the distance error for target incline due to the relative position and attitude between a camera and a target in miniature scale. In addition, the findings of an experiment in an outdoor environment demonstrate that the proposed measurement system has accuracy within 1 m at a range of 20-100 m which is the acceptable accuracy for automatic berthing.

• Journal of Biomedical Engineering Research
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• v.35 no.2
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• pp.14-18
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• 2014

This study is about e-Book program based on human-computer interaction(HCI) system for physically handicapped person. By acquiring background knowledge of HCI, we know that if we use vision-based interface we can replace current computer input devices by extracting any characteristic point and tracing it. We decided betweeneyes as a characteristic point by analyzing facial input image using webcam. But because of three-dimensional structure of glasses, the person who is wearing glasses wasn't suitable for tracing between-eyes. So we changed characteristic point to the bridge of the nose after detecting between-eyes. By using this technique, we could trace rotation of head in real-time regardless of glasses. To test this program's usefulness, we conducted an experiment to analyze the test result on actual application. Consequently, we got 96.5% rate of success for controlling e-Book under proper condition by analyzing the test result of 20 subjects.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.1
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• pp.1-7
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• 2016

ADAS (Advanced Driver Assistance Systems) requires not only real-time robust lane detection, both straight and curved, but also predicting upcoming steering direction by detecting the curvature of lanes. In this paper, a curvature lane detection algorithm is proposed to enhance the accuracy and detection rate based on using inverse perspective images and Gaussian Mixture Model (GMM) to segment the lanes from the background under various illumination condition. To increase the speed and accuracy of the lane detection, this paper used template matching, RANSAC and proposed post processing method. Through experiments, it is validated that the proposed algorithm can detect both straight and curved lanes as well as predicting the upcoming direction with 92.95% of detection accuracy and 50fps speed.

• Journal of the Korea Society of Computer and Information
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• v.16 no.11
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• pp.9-15
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• 2011

In this paper, we design and implement of gate management system by face recognition using smart phone. We investigate various algorithms for face recognition on smart phones. First step in any face recognition system is face detection. We investigated algorithms like color segmentation, template matching etc. for face detection, and Eigen & Fisher face for face recognition. The algorithms have been first profiled in MATLAB and then implemented on the Android phone. While implementing the algorithms, we made a tradeoff between accuracy and computational complexity of the algorithm mainly because we are implementing the face recognition system on a smart phone with limited hardware capabilities.

• Journal of Institute of Control, Robotics and Systems
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• v.18 no.8
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• pp.744-749
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• 2012

In this paper, we suggest that how to improve an accuracy of mobile robot's localization by using the sensor network information which fuses the machine vision camera, encoder and IMU sensor. The heading value of IMU sensor is measured using terrestrial magnetism sensor which is based on magnetic field. However, this sensor is constantly affected by its surrounding environment. So, we isolated template of ceiling using vision camera to increase the sensor's accuracy when we use IMU sensor; we measured the angles by pattern matching algorithm; and to calibrate IMU sensor, we compared the obtained values with IMU sensor values and the offset value. The values that were used to obtain information on the robot's position which were of Encoder, IMU sensor, angle sensor of vision camera are transferred to the Host PC by wireless network. Then, the Host PC estimates the location of robot using all these values. As a result, we were able to get more accurate information on estimated positions than when using IMU sensor calibration solely.

• Journal of IKEEE
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• v.16 no.4
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• pp.356-363
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• 2012

Information technology improves convenience, safety, and performance of automobiles. Recently, a lot of algorithms are studied to provide safety and environment information for driving, and traffic sign recognition is one of them. It can provide important information for safety driving. In this paper, we propose a method for traffic sign detection and identification concentrating on reducing the computation time. First, potential traffic signs are segmented by color threshold, and a polygon approximation algorithm is used to detect appropriate polygons. The potential signs are compared with the template signs in the database using SURF and ORB feature matching method.

• 한국HCI학회:학술대회논문집
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• 2008.02c
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• pp.172-177
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• 2008

Biometrics is essential for person identification because of its uniqueness from each individuals. Face recognition technology has advantage over other biometrics because of its convenience and non-intrusive characteristics. In this paper, we will present a overview of face recognition technology including face detection, feature extraction, and face recognition system. For face detection, we will describe template based method and face component based approach. PCA and LDA approach will be discussed for feature extraction, and nearest neighbor classifiers -will be covered for matching. Large database and the standardized performance evaluation methodology is essential in order to support state-of-the-art face recognition system. Also, 3D based face recognition technology is the key solution for the pose, lighting and expression variations in many applications.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.24 no.8B
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• pp.1490-1499
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• 1999

This paper proposes a new handwritten numeral recognition method using numeral shape grasps and FSOM (Fuzzy Self-Organizing Map). The proposed algorithm is based on the idea that numeral input data with similar shapes are classified into the same class. Shapes of numeral data are created using lines of external-contact and the class of numeral data is determined by template matching of the shapes. Each class of numeral data has FSOM and feature extraction method, respectively. In this paper, we divide the numeral database into the 16 classes. The divided FSOM model allows not only an independent learning phase of SOM but also step-by-step learning. Experiments using Concordia University handwritten numeral database proved that the proposed algorithm is effective to improve recognition accuracy.