• Korean Journal of Remote Sensing
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• v.33 no.6_1
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• pp.1019-1027
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• 2017

As high resolution satellite images can be used, numerous studies have been carried out for exploiting these images in various fields. This paper proposes horse hoof shaped object detection method based on mathematical morphology to extract interesting targets. Interesting targets have conceptually similar shapes such as a horse hoof, not having exact size or shape. Detection of an object with the similar shapes is possible by applying mathematical morphology processes. The proposed method allows an automatic object detection system to detect the meaningful object in a large satellite image rapidly. The mathematical morphology process can be applied to binary images, and thus this method is very simple. Therefore, this method can easily extract a "horse hoof shaped object" from any image that has indistinct edges of the interesting object and different image qualities depending on the filming location, filming time, and filming environment. Using the proposed method by which a "horse hoof shaped object" can be rapidly extracted, the performance of the automatic object detection system can be improved.

• International Journal of Control, Automation, and Systems
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• v.4 no.1
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• pp.10-16
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• 2006

In this paper, moving a fragile object from an initial point to a specific location in the minimum time without damage is studied. In order to achieve this goal, initially, the maximum acceleration and velocity ranges are specified. These ranges can be dynamically generate on the planned path by the manipulator. The path can be altered by considering the geometrical constraints. Later, considering the impulsive force constraint on the object, the range of maximum acceleration and velocity are obtained to preserve object safety while the manipulator is carrying it along the curved path. Finally, a time-optimal trajectory is planned within the maximum allowable range of acceleration and velocity. This time-optimal trajectory planning can be applied to real applications and is suitable for both continuous and discrete paths.

• Journal of information and communication convergence engineering
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• v.21 no.4
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• pp.329-336
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• 2023

This paper introduces an edge AI-based scene-specific object detection system for long-term traffic management, focusing on analyzing congestion and movement via cameras. It aims to balance fast processing and accuracy in traffic flow data analysis using edge computing. We adapt the YOLOv5 model, with four heads, to a scene-specific model that utilizes the fixed camera's scene-specific properties. This model selectively detects objects based on scale by blocking nodes, ensuring only objects of certain sizes are identified. A decision module then selects the most suitable object detector for each scene, enhancing inference speed without significant accuracy loss, as demonstrated in our experiments.

• Journal of the Semiconductor & Display Technology
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• v.12 no.1
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• pp.1-7
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• 2013

Grey-level statistical models have been widely used in many applications for object location and identification. However, conventional models yield some problems in model refinement when training images are not properly aligned, and have difficulties for real-time recognition of arbitrarily rotated models. This paper presents improved grey-level statistical models that align training images using image or feature matching to overcome problems in model refinement of conventional models, and that enable real-time recognition of arbitrarily rotated objects using efficient hierarchical search methods. Edges or features extracted from a mean training image are used for accurate alignment of models in the search image. On the aligned position and orientation, fitness measure based on grey-level statistical models is computed for object recognition. It is demonstrated in various experiments in PCB inspection that proposed methods are superior to conventional methods in recognition accuracy and speed.

• Journal of the Korea Society of Computer and Information
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• v.11 no.1 s.39
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• pp.87-96
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• 2006

Selectivity estimation is one of the query optimization techniques. It is difficult for the previous selectivity estimation techniques for moving objects to apply the position change of moving objects to synopsis. Therefore, they result in much error when estimating selectivity for queries, because they are based on the extended spatial synopsis which does not consider the property of the moving objects. In order to reduce the estimation error, the existing techniques should often rebuild the synopsis. Consequently problem occurs, that is, the whole database should be read frequently. In this paper, we proposed a moving object histogram method based on quad tree to develop a selectivity estimation technique for moving object queries. We then analyzed the performance of the proposed method through the implementation and evaluation of the proposed method. Our method can be used in various location management systems such as vehicle location tracking systems, location based services, telematics services, emergency rescue service, etc in which the location information of moving objects changes over time.

• Journal of Broadcast Engineering
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• v.7 no.3
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• pp.248-261
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• 2002

In this paper, we proposed a new 3-dimensional(3-D) object-tracking algorithm that can control a stereo camera using a variable window mask supported by which uses ,B-D information and an optical BPEJTC. Hence, three-dimensional information characteristics of a stereo vision system, distance information from the stereo camera to the tracking object. can be easily acquired through the elements of a stereo vision system. and with this information, we can extract an area of the tracking object by varying window masks. This extractive area of the tracking object is used as the next updated reference image. furthermore, by carrying out an optical BPEJTC between a reference image and a stereo input image the coordinates of the tracking objects location can be acquired, and with this value a 3-D object tracking can be accomplished through manipulation of the convergence angie and a pan/tilt of a stereo camera. From the experimental results, the proposed algorithm was found to be able to the execute 3-D object tracking by extracting the area of the target object from an input image that is independent of the background noise in the stereo input image. Moreover a possible implementation of a 3-D tele-working or an adaptive 3-D object tracker, using the proposed algorithm is suggested.

• Journal of the Korea Society of Computer and Information
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• v.8 no.1
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• pp.51-59
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• 2003

It is effective to be located in the double nodes in the distributed object replication systems, then object which nodes share is the same contents. The nodes store an access information on their local cache as it access to the system. and then the nodes fetch and use it, when it needed. But with time the coherence Problems will happen because a data carl be updated by other nodes. So keeping the coherence of the system we need a mechanism that we managed the to improve to improve the performance and availability of the system effectively. In this paper to keep coherence in the shared memory condition, we can set the limited parallel performance without the additional cost except the coherence cost using it to keep the object at the proposed adaptive duplication object(ADO) algorithms. Also to minimize the coherence maintenance cost which is the bi99est overhead in the duplication method, we must manage the object effectively for the number of replication and location of the object replica which is the most important points, and then it determines the cos. And that we must study the adaptive duplication object management mechanism which will improve the entire run time.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1402-1407
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• 2004

Moving a fragile object from an initial point to a goal location in minimum time without damage is pursued in this paper. In order to achieve the goal, first of all, the range of maximum acceleration and velocity are specified, which the manipulator can generate dynamically on the path that is planned a priori considering the geometrical constraints. Later, considering the impulsive force constraint of the object, the range of maximum acceleration and velocity are going to be obtained to keep the object safe while the manipulator is carrying it along the curved path. Finally, a time-optimal trajectory is planned within the maximum allowable range of the acceleration and velocity. This time optimal trajectory planning can be applied for real applications and is suitable for not only a continuous path but also a discrete path.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• v.2
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• pp.83-88
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• 2006

Many applications in the area of location-based services and personal navigation require nowadays the location determination of a user not only in outdoor environment but also indoor. To locate a person or object in a building, systems that use either infrared, ultrasonic or radio signals, and visible light for optical tracking have been developed. The use of WiFi for location determination has the advantage that no transmitters or receivers have to be installed in the building like in the case of infrared and ultrasonic based location systems. WiFi positioning technology adopts IEEE802.11x standard, by observing the radio signals from access points installed inside a building. These access points can be found nowadays in our daily environment, e.g. in many office buildings, public spaces and in urban areas. The principle of operation of location determination using WiFi signals is based on the measurement of the signal strengths to the surrounding available access points at a mobile terminal (e.g. PDA, notebook PC). An estimate of the location of the terminal is then obtained on the basis of these measurements and a signal propagation model inside the building. The signal propagation model can be obtained using simulations or with prior calibration measurements at known locations in an offline phase. The most common location determination approach is based on signal propagation patterns, namely WiFi fingerprinting. In this paper the underlying technology is briefly reviewed followed by an investigation of two WiFi positioning systems. Testing of the system is performed in two localization test beds, one at the Vienna University of Technology and the second at the Hong Kong Polytechnic University. First test showed that the trajectory of a moving user could be obtained with a standard deviation of about ${\pm}$ 3 m.

• Smart Media Journal
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• v.5 no.1
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• pp.88-94
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• 2016

In this paper, we proposed a new object tracking algorithm based on sparse representation to handle the drifting problem. In APG-L1(accelerated proximal gradient) tracking, the sparse representation is applied to model the appearance of object using linear combination of target templates and trivial templates with proper coefficients. Also, the particle filter based on affine transformation matrix is applied to find the location of object and APG method is used to minimize the l1-norm of sparse representation. In this paper, we make use of the trivial template coefficients actively to block the drifting problem. We experiment the various videos with diverse challenges and the result shows better performance than others.