• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2007.06a
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• pp.819-822
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• 2007

In this paper, we propose an object-tracking of mobile robots using CHT(Circular Hough transform) algorithm. The proposed method extracts the region of moving objects using 1-D projection algorithm, and detects circular objects using CHT. In order to verify the effectiveness of the proposed tracking method, we perform experiments of ball shape object-tracking using mobile robot based on ARM processor with CMOS camera.

• Journal of the Korea Society of Computer and Information
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• v.28 no.1
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• pp.93-101
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• 2023

In this paper, we propose a method of creating a 3D bounding box for an object using a vanishing point to increase the accuracy of object recognition in an image when recognizing an traffic object using a video camera. Recently, when vehicles captured by a traffic video camera is to be detected using artificial intelligence, this 3D bounding box generation algorithm is applied. The vertical vanishing point (VP1) and horizontal vanishing point (VP2) are derived by analyzing the camera installation angle and the direction of the image captured by the camera, and based on this, the moving object in the video subject to analysis is specified. If this algorithm is applied, it is easy to detect object information such as the location, type, and size of the detected object, and when applied to a moving type such as a car, it is tracked to determine the location, coordinates, movement speed, and direction of each object by tracking it. Able to know. As a result of application to actual roads, tracking improved by 10%, in particular, the recognition rate and tracking of shaded areas (extremely small vehicle parts hidden by large cars) improved by 100%, and traffic data analysis accuracy was improved.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.45 no.4
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• pp.10-21
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• 2008

The present paper propose a real-time moving object recognition and tracking method using the wavelet-based neural network and invariant moments. Candidate moving region detection phase which is the first step of the proposed method detects the candidate regions where a pixel value changes occur due to object movement based on the difference image analysis between continued two image frames. The object recognition phase which is second step of proposed method recognizes the vehicle regions from the detected candidate regions using wavelet neurual-network. From object tracking Phase which is third step the recognized vehicle regions tracks using matching methods of wavelet invariant moments bases to recognized object. To detect a moving object from image sequence the candidate regions detection phase uses an adaptive thresholding method between previous image and current image as result it was robust surroundings environmental change and moving object detections were possible. And by using wavelet features to recognize and tracking of vehicle, the proposed method decrease calculation time and not only it will be able to minimize the effect in compliance with noise of road image, vehicle recognition accuracy became improved. The result which it experiments from the image which it acquires from the general road image sequence and vehicle detection rate is 92.8%, the computing time per frame is 0.24 seconds. The proposed method can be efficiently apply to a real-time intelligence road traffic surveillance system.

• Journal of KIISE:Databases
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• v.32 no.1
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• pp.71-85
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• 2005

Various researches on moving object modeling, uncertainty processing, and moving object indexing have been tarried out in the field of moving object databases. However. previous location tracking systems cannot efficiently retrieve location data of vehicles, because they manage all location information of vehicles using the conventional database. In this paper, we design the vehicle location management systen that is able to manage and retrieve vehicle locations efficiently in mobile environment. The proposed system consists of a server for managing vehicle locations and mobile clients. The system is able to not only process spatiotemporal queries related to locations of moving vehicles but also Provide moving vehicles' locations which are not stored in the system. The system is also able to manage vehicle location data effectively using a moving object index.

• Journal of Intelligence and Information Systems
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• v.8 no.2
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• pp.1-13
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• 2002

In this paper, we propose an object tracking system which can be convinced of moving area shaped on objects through color sequential images, decided moving directions of foot messengers or vehicles of image sequences. In static camera, we suggests a new evaluating method extracting co-occurrence matrix with feature vectors of RGB after analyzing and blocking difference images, which is accessed to field of camera view for motion. They are energy, entropy, contrast, maximum probability, inverse difference moment, and correlation of RGB color vectors. we describe how to analyze and compute corresponding relations of objects between adjacent frames. In the clustering, we apply an algorithm of FCM(fuzzy c means) to analyze matching and clustering problems of adjacent frames of the featured vectors, energy and entropy, gotten from previous phase. In the matching phase, we also propose a method to know correspondence relation that can track motion each objects by clustering with similar area, compute object centers and cluster around them in case of same objects based on membership function of motion area of adjacent frames.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.6
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• pp.3104-3120
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• 2017

The intelligent monitoring system has been successfully applied in many fields such as: monitoring of production lines, transportation, etc. Smart surveillance systems have been developed and proven effective in some specific areas such as monitoring of human activity, traffic, etc. Most of critical application monitoring systems involve object tracking as one of the key steps. However, task of tracking of moving object is not easy. In this paper, the authors propose a method to implement human object tracking in outdoor environment based on human features in shearlet domain. The proposed method uses shearlet transform which combines the human features with context-sensitiveness in order to improve the accuracy of human tracking. The proposed algorithm not only improves the edge accuracy, but also reduces wrong positions of the object between the frames. The authors validated the proposed method by calculating Euclidean distance and Mahalanobis distance values between centre of actual object and centre of tracked object, and it has been found that the proposed method gives better result than the other recent available methods.

• The Journal of the Korea institute of electronic communication sciences
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• v.10 no.8
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• pp.867-874
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• 2015

Hoist have been installed at wharfs or seashore in the center of fishing village fraternities. A Hoist is used in harbor loading and unloading fishing gear or seafoods and is a device to refloat fishing boats into a breakwater or land in case of typhoon or bad weather. In this paper, we propose image perception and moving objects tracking system that detects boat's damage, theft and trespassing occurred at the wharf. This system detects objects' motion in real time by using the motion templet and tracks to concentrate on a moving object(person, boat, etc.) by using a PTZ camera.

• Journal of Korea Society of Digital Industry and Information Management
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• v.14 no.1
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• pp.77-85
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• 2018

This paper proposes a robust digital video stabilization algorithm to extract and track an object, which uses a phase correlation-based motion correction. The proposed video stabilization algorithm consists of background stabilization based on motion estimation and extraction of a moving object. The motion vectors can be estimated by calculating the phase correlation of a series of frames in the eight sub-images, which are located in the corner of the video. The global motion vector can be estimated and the image can be compensated by using the multiple local motions of sub-images. Through the calculations of the phase correlation, the motion of the background can be subtracted from the former frame and the compensated frame, which share the same background. The moving objects in the video can also be extracted. In this paper, calculating the phase correlation to track the robust motion vectors results in the compensation of vibrations, such as movement, rotation, expansion and the downsize of videos from all directions of the sub-images. Experimental results show that the proposed digital image stabilization algorithm can provide continuously stabilized videos and tracking object movements.

• Journal of the Korea Society of Computer and Information
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• v.12 no.5
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• pp.163-170
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• 2007

In this paper, We propose a new technique for extraction of moving objects included in compressed video signal. Moving object extraction is used in several fields such as contents based retrieval and target tracking. In this paper, in order to extract moving object blocks, motion vectors and DCT coefficients are used selectively. The proposed algorithm has a merit that it is no need of perfect decoding, because it uses only coefficients on the DCT transform domain. We used three test video sequences in the computer simulation, and obtained satisfactory results.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.98.6-98
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• 2002

1. Introduction 2. Detection of the moving object 3. Correspondence problem 4. Experiment 5. Conclusions. References