• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.24 no.6
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• pp.703-709
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• 2015

In this work, a robot aimed at grapping and delivering an object by using a simple finger-pointing command from a hand- or arm-handicapped person is introduced. In this robot system, a Leap Motion sensor is utilized to obtain the finger-motion data of the user. In addition, a Kinect sensor is also used to measure the 3D (Three Dimensional)-position information of the desired object. Once the object is pointed at through the finger pointing of the handicapped user, the exact 3D information of the object is determined using an image processing technique and a coordinate transformation between the Leap Motion and Kinect sensors. It was found that the information obtained is transmitted to the robot controller, and that the robot eventually grabs the target and delivers it to the handicapped person successfully.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.01a
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• pp.547-550
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• 2009

The object recognition mechanism of human being is not well understood yet. On research of animal experiment using an ape, however, neurons that respond to simple shape (e.g. circle, triangle, square and so on) were found. And Hypothesis has been set up as human being may recognize object as combination of such simple shapes. That mechanism is called Figure Alphabet Hypothesis, and those simple shapes are called Figure Alphabet. As one way to research object recognition algorithm, we focused attention to this Figure Alphabet Hypothesis. Getting idea from it, we proposed the feature extraction algorithm for object recognition. In this paper, we described recognition of binarized images of multifont alphabet characters by the recognition model which combined three-layered neural network in the feature extraction algorithm. First of all, we calculated the difference between the learning image data set and the template by the feature extraction algorithm. The computed finite difference is a feature quantity of the feature extraction algorithm. We had it input the feature quantity to the neural network model and learn by backpropagation (BP method). We had the recognition model recognize the unknown image data set and found the correct answer rate. To estimate the performance of the contriving recognition model, we had the unknown image data set recognized by a conventional neural network. As a result, the contriving recognition model showed a higher correct answer rate than a conventional neural network model. Therefore the validity of the contriving recognition model could be proved. We'll plan the research a recognition of natural image by the contriving recognition model in the future.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.1
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• pp.15-21
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• 2023

This paper is a study on the development of an artificial intelligence model that recognizes a hole cup on a golf green. A CNN-based object detection algorithm was used to recognize the hole cup on the green. Also, Apple's CreateML was used to create a model of the object detection algorithm. This paper created a JSON file with 120 training images and annotations to meet the needs of CreateML. In addition, for more accurate learning, data amplification algorithm was used for learning data and 288 learning data were used for learning. By changing the Iterations, Batch size, and Grid size required by CreateML, we found parameter values that improve the performance of the model. A prototype app was developed by applying the developed model, and performance was measured on an actual golf course green using the prototype app. As a result of the measurement, it was found that the hole cup was accurately recognized within 10m, which is the typical golfer's putting distance.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1994-1999
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• 2003

This paper discusses dynamic characteristics of motion of a pair of multi-degrees of freedom robot fingers executing grasp of a rigid object and controlling its orientation with the aid of rolling contacts. In particular, the discussions are focused on a problem of gain-tuning of sensory feedback signals proposed from the viewpoint of sensorymotor coordination, which consist of a feedforward term, a feedback term for controlling rotational moment of the object, and another term for controlling its rotational angle. It is found through computer simulations of the overall fingersobject dynamics subject to rolling contact constraints that some dynamic characteristics of torque-angular velocity relation may play an important role likely as reported by experimental results in muscle physiology and therefore selection of damping gains in angular velocity feedback depending on the guess of object mass is crucial. Finally, a guidance of gain-tuning in each feedback term is suggested and its validity is discussed by various computer simulations.

• Journal of Advanced Marine Engineering and Technology
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• v.27 no.5
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• pp.590-599
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• 2003

In this study. object transport method based on ultrasonic flexural vibration is presented. Ultrasonic vibration generates ultrasonic traveling waves on the surface of elastic medium. Objects are transported through the interaction with traveling waves propagating in medium. Two types of transport methods are studied： frictional drive and acoustic levitation. With frictional drive, objects are transported in contact with the beam in the opposite direction of wave propagation whereas with acoustic levitation, objects are acoustically levitated above the beam surface and transported in the wave propagation direction. Transport characteristics are experimentally investigated using objects of different shapes and sizes. The transition from acoustic levitation mode to frictional drive mode is also examined. and it is found to occur when the ratio of mass to area of an object exceeds the threshold ratio of mass to area. It is envisaged that this feasibility study will serve as a stepping-stone for ultrasonic vibration to become an effective industrial material handling device in the future.

• Journal of Multimedia Information System
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• v.6 no.4
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• pp.173-178
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• 2019

Mongolian historical and cultural monuments on settlement areas of stone inscriptions, stone images, rock-drawings, remains of cities, architecture are still telling us their stories. These monuments depict the understanding of the word, philosophical and artistic outlook, beliefs, religion, national art, language, culture and traditions of Mongols [1]. Nowadays computer science, especially computer vision is applying in the other science fields. The main problem is how to apply and which algorithm can detect and classify the objects correctly. In this paper, we propose a method to detect object from Mongolian nomadic environment images. This work proposes a method for object detection that is the combination of the binary operations in the edge detection results. We found out the best method and parameters of state-of-the-art machine learning algorithms. In experimental result, we evaluate our results with 10-fold cross validation and split 66% strategies.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.543-546
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• 1996

We propose a new visual tracking system for grasping which can find grasping points of an unknown polygonal object. We construct the system with the image prediction technique and Extended Kalman Filter algorithm. The Extended Kalman Filter(EKF) based on the SVD can improve the accuracy and processing time for the estimation of the nonlinear state variables. By using it, we can solve the numerical unstability problem that can occur in the visual tracking system based on Kalman filter. The image prediction algorithm can reduce the effect of noise and the image processing time. In the processing of a visual tracking, we can construct the parameterized family and can found the grasping points of unknown object through the geometric properties of the parameterized family.

• The Bulletin of The Korean Astronomical Society
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• v.39 no.2
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• pp.82-82
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• 2014

One of the subjects in clouds' structure and development is small scale structure of interstellar cloud. The possibility of AU scale structure (Marscher et al. 1993; Moore & Marscher 1995; Roy et al. 2012) is discussed, and this small scale structure is considered as the result of hydrogen volume density (Moore & Marscher 1995), or small-scale chemical and other inhomogeneities (Liszt & Lucas 2000). In order to study this subject with emission line, extremely high resolution is mandatory by VLBI system. However, the alternative method could be observing the absorption line of interstellar cloud on the continuum object. In this case, the resolution would be restricted to the size of the continuum object, if the size of the object is smaller than the resolution of a used telescope. We observed the previous researchers' three objects (BLLAC, NRAO150, B0528+138), whose spectrums are changed from 1993 to 1998 (Liszt & Lucas 2000), with KVN. Through KVN observation, we found the changes of optical depth spectrum compared with the previous spectrums. We will discuss the optical depth spectrum variation by time variation and the meaning of it.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.25.3-25
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• 2001

This paper describes a control method of a robot cooperating with a human. A task in which a robot and a human move an object cooperatively is considered. To develop the force controller of the robot, the characteristics of human arm are investigated. The arm is forced to move along a trajectory in the experiment and the exerted force and the displacement are analyzed, It is found the force characteristics of the human arm is regarded as an optimal damper with minimizing a cost function. Then, the model is implemented to a robot and the cooperation of the robot and a human operator is examined. The effectiveness of the derived model is investigated and the experimental results show that the human moves the object supported by the robot with a minimum jerk trajectory.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.40 no.1
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• pp.51-62
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• 2003

A new video segmentation algorithm for segmentation-based video coding is proposed. The method uses a new criterion based on similarities in both motion and brightness. Brightness and motion information are incorporated in a single segmentation procedure. The actual segmentation is accomplished using a region-growing technique based on the watershed algorithm. In addition, a tracking technique is used in subsequent frames to achieve a coherent segmentation through time. Simulation results show that the proposed method is effective in determining object boundaries not easily found using the statistic criterion alone.