• Proceedings of the IEEK Conference
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• 1999.06a
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• pp.1045-1048
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• 1999

In this paper, we calculate the moving velocity of viewer by using two eye images obtained at different time through the camera. This process is necessary for future 3D display technique, in which moving viewer can see 3D image continuously We firstly extract two eyes image and calculate the pixel coordinate of center point between two eyes. Next, we calculate the moving velocity in two dimension by comparing two center point coordinates obtained at different time.

• Journal of information and communication convergence engineering
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• v.7 no.4
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• pp.551-555
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• 2009

This paper proposes a signal generation method for automatic control of a monitoring camera. Using the control signal, the monitoring camera can track a moving object and keep it near the image center for a longer time. The proposed method is estimated in the experiments that automatically move a maker located at the specified position to the image center.

• Journal of the Korean Society for Precision Engineering
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• v.15 no.7
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• pp.175-181
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• 1998

This paper describes realtime visual tracking system of moving object for three dimensional target using EKF(Extended Kalman Filter). We present a new realtime visual tracking using EKF algorithm and image prediction algorithm. We demonstrate the performance of these tracking algorithm through real experiment. The experimental results show the effectiveness of the EKF algorithm and image prediction algorithm for realtime tracking and estimated state value of filter, predicting the position of moving object to minimize an image processing area, and by reducing the effect by quantization noise of image.

• Journal of Industrial Technology
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• v.21 no.B
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• pp.91-98
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• 2001

In this paper, center detection and motion analysis of a moving object are studied. Kohonen's self-organizing neural network models are used for the moving objects tracking and time delay neural networks are used for dynamic characteristic analysis. Instead of objects brightness, neuron projections by Kohonen Networks are used. The motion of target objects can be analyzed by using the differential neuron image between the two projections. The differential neuron image which is made by two consecutive neuron projections is used for center detection and moving objects tracking. The two differential neuron images which are made by three consecutive neuron projections are used for the moving trajectory estimation. It is possible to distinguish 8 directions of a moving trajectory with two frames and 16 directions with three frames.

• Journal of information and communication convergence engineering
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• v.9 no.6
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• pp.747-752
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• 2011

The position detection of overlapping area in the interframe for image stitching using auto and cross correlation function (ACCF) and compounding one image with the stitching algorithm is presented in this paper. ACCF is used by autocorrelation to the featured area to extract the filter mask in the reference (previous) image and the comparing (current) image is used by crosscorrelation. The stitching is detected by the position of high correlation, and aligns and stitches the image in shifting the current image based on the moving vector. The ACCF technique results in a few computations and simplicity because the filter mask is given by the featuring block, and the position is enabled to detect a bit movement. Input image captured from CMOS is used to be compared with the performance between the ACCF and the window correlation. The results of ACCF show that there is no seam and distortion at the joint parts in the stitched image, and the detection performance of the moving vector is improved to 12% in comparison with the window correlation method.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2002.04a
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• pp.500-504
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• 2002

The purpose of this paper is to implement a guidance system for an object on the road. A watch camera equipped on the auto door recognizes the direction for the destination of an object, after that it determines whether opening or closing the door, and then the door is opened automatically, based on the decision. The motion of the moving object is approximated by using the technique of the image processing of tracking images and the affine model. The direction of the moving object is predicted from image information obtained by applying linear Kalman filter to the motion estimation in order to reduce the search region, the moving position, and the direction of the center of the object. Along with the guidance function, the system has the announcing function to the object. The experimental results confirm the veridity and applicability of the proposed system.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.19 no.4
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• pp.639-648
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• 1994

This paper presents a new block matching algorithm in estimation of motion information that is important technology in compressing interframe. In estimation of motion information, we find differential image using two successive frame image in order to find required real time processing and accurate moving vector, the binary image is made of edge and find more accurate moving vectors by application quadtree method to parts including many moving according to this activity. The computer simulation results show that increased PSNR and reduced computation time.

• Proceedings of the Korea Institute of Convergence Signal Processing
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• 2001.06a
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• pp.217-220
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• 2001

In this paper, we propose a segmentation method of moving object using the spatio-temporal information in image sequences. Proposed method consists of motion detection step using difference image, region segmentation step using k-means algorithm, motion estimation step and segmenting step using intensity and motion information. Experimental results show that the method is capable of segmenting variously moving objects in image sequences.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.17 no.2
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• pp.110-116
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• 2005

This paper deals with interaction between two bubbles or particles and flow around them, visualized by a moving object flow image analyzer(MOFIA) consisting of a three-dimensional (3D) moving object image analyzer(MOIA) and two-dimensional particle image velocimetry(PIV). The experiments were carried out for rising bubbles or particles of various densities, sizes, and/or shapes in stagnant water in a vertical pipe. In the MOFIA employed, 3D-MOIA was used to measure particles or bubbles motion and PIV was used to measure fluid flow, The experimental results showed that the interaction was characterized by the shape, size and density of two particles or bubbles.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.11 no.1
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• pp.1-15
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• 1986

Optic flow is 2D velocity projected on the image plane of 3D velocity of a moving surface element. In this paper, we survey techniques computing optic flows from an image time sequence of moving objects and techniques determining 3D velocities and surface structures of the moving objects from the optic flows determined.