• International Journal of Advanced Culture Technology
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• v.6 no.4
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• pp.317-322
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• 2018

We use edge detection technique for the input image to extract the entire edges of the object in the image and then select only the edges that construct the outline of the object. By examining the positional relation between these pixels composing the outline, a simplified version of the outline of the object in the input image is generated by removing unnecessary pixels while maintaining the condition of connection of the outline. For each pixel constituting the outline, its direction is calculated by examining the positional relation with the next pixel. Then, we group the consecutive pixels with same direction into one and then change them to a line segment instead of a point. Among those line segments composing the outline of the object, a line segment whose length is smaller than a predefined minimum length of acceptable line segment is removed by merging it into one of the adjacent line segments. As a result, an outline composed of line segments of over a certain length is obtained through this process.

• Journal of the Korea Society of Computer and Information
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• v.3 no.1
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• pp.81-94
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• 1998

In order to extract the contour of interesting object in the image, Kass suggested the Active Contour Model called "Snakes". Snakes is a model which defines the contour of image energy. It also can find the contour of object by minimizing these energy functions. The speed of this model is slow and this model is sensitive of initialization. In order to improve these problems, Gunn extracted the accurate contour by using two initialization. and operated to less sensitive of initialization. This method could extract more accurate contour than the existing method, but it had no effect in the speed and it was sensitive of noise. This paper applied to the Energy Minimization Algorithm about only the pixel within the window applying the window of 8$\times$8 size at each contour point consisting Snakes in order to solve these problems. The method offered in this paper is applied to extract the contour of original image and cup image added to gaussian noise. By tracking the face using this offered method, it is applied to virtual reality and motion tracking. tracking.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.24 no.5
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• pp.861-870
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• 2014

According to the intelligence of the malicious code to extract the executable file in physical memory is emerging as an import researh issue. In previous physical memory studies on executable file extraction which is targeting running files, they are not extracted as same as original file saved in disc. Therefore, we need a method that can extract files as same as original one saved in disc and also can analyze file-information loaded in physical memory. In this paper, we provide a method that executable file extraction by analyzing information of Windows kernel file object. Also we analyze the characteristic of physical memory loaded file data from the experiment and we demonstrate superiority because the suggested method can effectively extract more of original file data than the existing method.

• Proceedings of the IEEK Conference
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• 2002.06d
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• pp.129-132
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• 2002

In this paper, we propose a 3-D animation system to track and analyze motion of the human object. The proposed system consists of two separate layers: motion analysis layer and 3-D model registration layer. Following the MPEG-4 SNHC standard, we generate object motion using body definition and animation parameters. In the implemented system, we acquire human motion data from a single camera and extract body definition parameters from arbitrary VRML human models.

• Proceedings of the IEEK Conference
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• 2006.06a
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• pp.1003-1004
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• 2006

In this paper we extract the position value of the tracking object using the hierarchical optic-digital algorithm and to control the main visual angle and Pan/Tilt. And then we propose the optic-digital stereo object tracking system for adaptive extracting the moving-target.

• Proceedings of the IEEK Conference
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• 2006.06a
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• pp.299-300
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• 2006

In this paper, we propose a segmentation algorithm which combines the ideas from local watershed transforms and the region merging algorithm based hierarchical queue. Only the process of watershed and region merging algorithm can be restricted area. A fast region merging approach is proposed to extract the video object from the regions of watershed segmentation. Results show the effectiveness and convenience of the approach.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.557-557
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• 2000

Tracking of the moving object, which is realized by the computer vision, is used for military and industrial fields. It is the application technique with imply complicated processing for understanding the input images. But, in these days, the most moving object tracking algorithms have many difficult problems. A typical problem is the increase of calculation time depending on target number. For this reason, there are many studies to solve real time processing problems and errors for background environmental change. In this paper, we used optical flow which is one of moving object tracking algorithms. It represents vector of the moving object. Optical flow estimation based on the regularization method depends on iteration method but it is very sensitive the noise. We proposed a new method using the Combinatorial Hough Transform (CHT) and Voting Accumulation in order to find optimal constraint lines. Also, we used the logical operation in order to release the operation time. The proposed method can easily and accurately extract the optical flow of moving object area and the moving information. We have simulated the proposed method using the test images. This images are included the noise. Experimental results show that the proposed method get better flow and estimate accurately the moving information.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• v.9 no.2
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• pp.408-413
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• 2005

This paper presents a technique which extracts a moving object from omni-directional images and estimates a real coordinates of the moving object using 3D parabolic coordinate transformation. To process real-time, a moving object was extracted by proposed Hue histogram Matching Algorithms. We demonstrate our proposed technique could extract a moving object strongly without effects of light changing and estimate approximation values of real coordinates with theoretical and experimental arguments.

• Proceedings of the IEEK Conference
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• 2001.06c
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• pp.77-80
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• 2001

In general, the informations of the inner image that user interested in are limited to a special domain. In this paper, as using Wavelet Transform for dividing image into high frequency and low frequency, We can separate foreground including many data. After calculating object boundary of separated part, We extract special features using Color Coherence Vector. According to results of this experiment, the method of comparing data extracting foreground features is more effective than comparing data extracting features of entire image when we extract the image user interested in.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.4 no.3
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• pp.126-133
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• 2003

This paper is related to a morphological segmentation method for extracting the moving object in video sequence using global motion compensation and two-dimensional spatio-temporal entropic thresholding. First, global motion compensation is performed with camera panning vector estimated in the hierarchical pyramid structure constructed by wavelet transform. Secondly, the regions with high possibility to include the moving object between two consecutive frames are extracted block by block from the global motion compensated image using two-dimensional spatio-temporal entropic thresholding. Afterwards, the LUT classifying each block into one among changed block, uncertain block, stationary block according to the results classified by two-dimensional spatio-temporal entropic thresholding is made out. Next, by adaptively selecting the initial search layer and the search range referring to the LUT, the proposed HBMA can effectively carry out fast motion estimation and extract object-included region in the hierarchical pyramid structure. Finally, after we define the thresholded gradient image in the object-included region, and apply the morphological segmentation method to the object-included region pixel by pixel and extract the moving object included in video sequence. As shown in the results of computer simulation, the proposed method provides relatively good segmentation results for moving object and specially comes up with reasonable segmentation results in the edge areas with lower contrast.