• The Journal of the Korea Contents Association
• /
• v.16 no.8
• /
• pp.395-403
• /
• 2016

Recently, Image processing has been used in many areas. In the image processing techniques that a lot of research is tracking of moving object in real time. There are a number of popular methods for tracking an object such as HOG(Histogram of Oriented Gradients) to track pedestrians, and Codebook to subtract background. However, object extraction has difficulty because that a moving object has dynamic background in the image, and occurs severe lighting changes. In this paper, we propose a method of object extraction using depth image and color image features based on ROI(Region of Interest). First of all, we look for the feature points using the color image after setting the ROI a range to find the location of object in depth image. And we are extracting an object by creating a new contour using the convex hull point of object and the feature points. Finally, we compare the proposed method with the existing methods to find out how accurate extracting the object is.

• Journal of Korea Society of Industrial Information Systems
• /
• v.13 no.4
• /
• pp.1-13
• /
• 2008

In this paper, we propose a method to solve a problem in binarizing the rear number plate image captured by a camera on a moving vehicle. An image may be shadowed by the cavernous structure of the rear side of a moving vehicle and it makes us hard to get a high quality of binary image. Therefore, we first detect a shadow edge and then divide an image into the shadow part and non-shadow part by the edge. Finally, the binary image is obtained by binarizing each part and merging them In this paper, we do comparative work on a group of binarization methods including our method, the method suggested by Zheng, the method using block binarization, and the method using labeling. The result shows that our method achieves better performance than others in most cases.

• Journal of the Institute of Electronics Engineers of Korea SP
• /
• v.49 no.4
• /
• pp.95-104
• /
• 2012

In the image captured by the camera in a moving vehicle, there exist various motions due to the change of background, motion of objects in the image that make difficult to extract a pure vibrational motion by the camera. In this paper, we suggest an image stabilization with the elimination of various motion components based on the classification of motions in the image by their characteristics. After the elimination of various local motions, images are compensated and stabilized with the global motion caused by the camera. Also, we suggest an accurate and fast image stabilization by excluding regions of little information based on block differences and edge densities.

• Journal of the Institute of Convergence Signal Processing
• /
• v.3 no.3
• /
• pp.6-13
• /
• 2002

In this paper, we propose an image processing based method to measure red-time and green-time backward moving shockwave speed automatically at signalized intersections. Shockwave means the discontinuous boundary line between different vehicle traffic flows, and its moving speed is called shockwave speed which is obtain from the slope of boundary line. In this paper, we compose distance-time diagram for measuring shockwave speed automatically. By global vehicle tracking, we draw all of the vehicle moving path on distance-time diagram. We analyze the slope change pattern of curved moving path line, and compute red-time and green-time backward moving shockwave speed. We obtain the measurement result of shockwave speed, when applying above mentioned proposed method to experiment at signalized intersections, Once we can measure the shockwave speed, we could apply the result to highway ramp metering and automatic signal control at intersections effectively since we know the situation of frontal congestion easily.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 1999.05a
• /
• pp.104-108
• /
• 1999

It is presented many effect that represented by implicated one image more than each images with a fragment meaning. ‘Mosaic’ is technique be applied at this situation. ‘Mosaic’ is created by complicated one new image which by multi image be eliminated overlap region. This research is development for mosaic system by multi image. The system is divided that shot segmentation and mosaic image creation. Shot segmentation divided that merge with respect to similarity images which video data of moving picture in sequence time and mosaic image creation is composed of one image with which all frames in segmented shot.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 1999.11a
• /
• pp.411-415
• /
• 1999

Image mosaic system is called that switching several image, or moving image into a image. In this paper, we represented that not image mosaic construction with respect to traditional and directional method but representing which mosaic system construction about using tree. Also, in this paper represent study that static image mosaic and dynamic image mosaic.

• Proceedings of the IEEK Conference
• /
• 2001.06c
• /
• pp.237-240
• /
• 2001

An image processing and decision making method for the Automatic Surveillance System is proposed. The aim of our Automatic Surveillance System is to detect a moving object and make a decision on whether it is human or not. Various object features such as the ratio of the width and the length of the moving object, the distance dispersion between the principal axis and the object contour, the eigenvectors, the symmetric axes, and the areas if the segmented region are used in this paper. These features are not the unique and decisive characteristics for representing human Also, due to the outdoor image property, the object feature information is unavoidably vague and inaccurate. In order to make an efficient decision from the information, we use a fuzzy rules base system ai an approximate reasoning method. The fuzzy rules, combining various object features, are able to describe the conditions for making an intelligent decision. The fuzzy rule base system is initially constructed by heuristic approach and then, trained and tasted with input/output data Experimental result are shown, demonstrating the validity of our system.

• Proceedings of the IEEK Conference
• /
• 2002.07a
• /
• pp.200-203
• /
• 2002

We suggest a novel approach to the tracking of multiple moving objects in image sequence. The tracking of multiple moving objects include some complex problems(crossing (occluding), entering, disappearing, joining, and dividing) for objects identifying. Our method can settle these problems by optimization of a penalty function and movement prediction. It is executable in .eat time processing (more than 30 ㎐) because it is computed by only location data.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
• /
• v.21 no.9
• /
• pp.32-38
• /
• 2007

In this study, a new algorithm for measuring the velocity and distance from a camera to a moving object by using pseudo-stereo images obtained from a single camera with a stereo adapter is proposed. The proposed system is similar to a parallel visual stereo system using a two-camera system, but because this system can obtain pseudo-stereo images form a single camera, it has advantages not only in the aspect of cost but also in stereo conformity by arrangement and the calibration of the left and right stereo cameras upon image processing.

• Proceedings of the KIEE Conference
• /
• 2005.07d
• /
• pp.2531-2533
• /
• 2005

The proposed neural network technique is the real time computation method based theory of inter-node diffusion for searching the safety distances from the sudden appearance-objects during the work driving. The main steps of the distance computation using the theory of stereo vision like the eyes of man is following steps. One is the processing for finding the corresponding points of stereo images and the other is the interpolation processing of full image data from nonlinear image data of objects. All of therm request much memory space and time. Therefore the most reliable neural-network algorithm is drived for real-time matching of obejects, which is composed of a dynamic programming algorithm based on sequence matching techniques in moving objects.