• Proceedings of the IEEK Conference
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• 2000.06d
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• pp.50-53
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• 2000

In this work, the new algorithm that automatically extracts moving object of the video image is presented. In order to extract moving object, it is that velocity vectors correspond to each frame of the video image. Using the estimated velocity vector, the position of the object are determined. the value of the coordination of the object is initialized to the seed, and in the image plane, the moving object is automatically segmented by the region growing method. As the result of an application in sequential images, it is available to extract a moving object.

• Journal of the Korean Institute of Telematics and Electronics C
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• v.34C no.10
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• pp.76-88
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• 1997

Based on the principles described in Part I, we have implemented a working prototype vision system using a feature structure called an LSG (local surface group) for generating object hypotheses. In order to verify an object hypothesis, we estimate the view of the hypothesized model object and render the model object for the computed view. The object hypothesis is then verified by finding additional features in the scene that match those present in the rendered image. Experimental results on synthetic and real range images show the effectiveness of the indexing scheme.

• IEIE Transactions on Smart Processing and Computing
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• v.3 no.6
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• pp.366-371
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• 2014

This paper reports a machine learning approach for image object detection. Object detection and localization in a wild image, such as a STL-10 image dataset, is very difficult to implement using the traditional computer vision method. A convolutional neural network is a good approach for such wild image object detection. This paper presents an object detection application using a convolutional neural network with pretrained feature vector. This is a very simple and well organized hierarchical object abstraction model.

• Journal of information and communication convergence engineering
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• v.12 no.4
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• pp.263-270
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• 2014

Corner detection and feature extraction are essential aspects of computer vision problems such as object recognition and tracking. Feature detectors such as Scale Invariant Feature Transform (SIFT) yields high quality features but computationally intensive for use in real-time applications. The Features from Accelerated Segment Test (FAST) detector provides faster feature computation by extracting only corner information in recognising an object. In this paper we have analyzed the efficient object detection algorithms with respect to efficiency, quality and robustness by comparing characteristics of image detectors for corner detector and feature extractors. The simulated result shows that compared to conventional SIFT algorithm, the object recognition system based on the FAST corner detector yields increased speed and low performance degradation. The average time to find keypoints in SIFT method is about 0.116 seconds for extracting 2169 keypoints. Similarly the average time to find corner points was 0.651 seconds for detecting 1714 keypoints in FAST methods at threshold 30. Thus the FAST method detects corner points faster with better quality images for object recognition.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.48 no.5
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• pp.16-22
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• 2011

This paper presents the multi-object tracking approach using the background difference and particle filtering by monte carlo sampling. We apply particle filters based on probabilistic importance sampling to multi-object independently. We formulate the object observation model by the histogram distribution using color information and the object dynaminc model for the object motion information. Our approach does not increase computational complexity and derive stable performance. We implement the whole Bayesian maximum likelihood framework and describes robust methods coping with the real-world object tracking situation by the observation and transition model.

• Journal of Korea Multimedia Society
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• v.8 no.9
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• pp.1239-1247
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• 2005

Basically, objects are discriminated by transfer functions in volume rendering . However, in some cases objects cannot be discriminated only with transfer functions. In these cases, objects are pre-segmented with other methods, and visualized based on the segmentation information. In this paper we present a way of assigning per-object transparency in visualization of segmented volumes. Semi-transparent rendering is used to effectively give context information about the observed object. Per-object transparency can be used as a very effective visualization tool especially when it is difficult to adjust transfer functions to make the object semi-transparent. We present several interpretations of the meaning of per-object transparency, and corresponding variations of the algorithm. We show that efficient implementations for interactive use are possible, by presenting an implementation using general graphics hardware.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.4
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• pp.786-792
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• 2007

Moving object tracking is very important in video surveillance system. This paper presents a method for tracking moving objects in an outdoor environment. To moving object tracking, first, after extract object that move yielding weight subtraction image and then use close operator to reduce the noise. And we track a object that move detected by matching the extracted multi-feature information. The proposed tracking technique can track moving object by multi-feature matching method so that exactly tracking the objects which are suddenly move or stop. The proposed tracking technique can be efficiently tracking the moving objects, because of combined with spatial position, shape and intensity informations.

• Journal of Information Technology Applications and Management
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• v.15 no.2
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• pp.1-14
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• 2008

The distinguished prosperity of information technologies from great progress of e-business during the last decade has unavoidably made software development for active data mining to discovery hidden predictive information regarding business trends and behavior from vary large databases. Therefore this paper develops an active mining object(ADMO) component, which provides real-time predictive information from web databases. The ADMO component is to extended ADO(ActiveX Data Object) component to active data mining component based on COM(Component Object Model) for application program interface(API). ADMO component development made use of window script component(WSC) based on XML(eXtensible Markup Language). For the purpose of investigating the application environments and the practical schemes of the ADMO component, experiments for diverse practical applications were performed in this paper. As a result, ADMO component confirmed that it could effectively extract the analytic information of classification and aggregation from vary large databases for Web services.

• Journal of Information Processing Systems
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• v.7 no.3
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• pp.519-530
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• 2011

A Snake is an active contour for representing object contours. Traditional snake algorithms are often used to represent the contour of a single object. However, if there is more than one object in the image, the snake model must be adaptive to determine the corresponding contour of each object. Also, the previous initialized snake contours risk getting the wrong results when tracking multiple objects in successive frames due to the weak topology changes. To overcome this problem, in this paper, we present a new snake method for efficiently tracking contours of multiple objects. Our proposed algorithm can provide a straightforward approach for snake contour rapid splitting and connection, which usually cannot be gracefully handled by traditional snakes. Experimental results of various test sequence images with multiple objects have shown good performance, which proves that the proposed method is both effective and accurate.

• Proceedings of the KSRS Conference
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• 2004.10a
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• pp.283-286
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• 2004

This paper refers and implements XML Web services, which supports networked interchanges of moving object information. XML Web services are expected to be fundamental building blocks in the move to distributed computing on the Internet. As an interchange format, GML encodes semantics, syntax, and schema of geospatial and geoprocessing-related information resources. It can give great benefits to utilize raw data easily as an XML encoding format does. This paper proposes a full coverage of interoperable location trajectory services consisting of 3 independent modules: a moving object database, a data processing server, and a web services interface module. For communications, SOAP protocols and WSDL documents are used, which can guarantee an interoperability of a system regardless of different platforms and service channels. This paper also designs a GML data format that represents location information of probe cars.