• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.5C
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• pp.505-513
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• 2009

This paper proposes a real-time foreground segmentation and background substitution method for protecting the privacy on visual communication. Previous works on this topic have some problems with the color and shape of foreground and the capture device such as stereo camera. we provide a solution which can segment the foreground in real-time using fixed mono camera. For improving the performance of a foreground extraction, we propose the Temporal Foreground Probability Model (TFPM) by modeling temporal information of a video. Also we provide an boundary processing method for natural and smooth synthesizing that using alpha matte and simple post-processing method.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37C no.9
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• pp.751-756
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• 2012

In this paper, we propose a foreground extraction and depth map generation method using a time-of-flight (TOF) depth camera. Although, the TOF depth camera captures the scene's depth information in real-time, it has a built-in noise and distortion. Therefore, we perform several preprocessing steps such as image enhancement, segmentation, and 3D warping, and then use the TOF depth data to generate the depth-discontinuity regions. Then, we extract the foreground object and generate the depth map as of the color image. The experimental results show that the proposed method efficiently generates the depth map even for the object boundary and textureless regions.

• 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.

• Proceedings of the Korea Multimedia Society Conference
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• 2002.11b
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• pp.118-121
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• 2002

The study on shilla monumental inscription has been accomplished by many historians. However, the research on segmentation of monumental inscription image using digital image processing is not sufficient for restoration of the image. Although, many image processing methods have been proposed for region extraction in still image, there is no suitable method for accurate interpretation of monumental inscription image. To distinguish foreground and background region in the image, this paper presents new segmentation algorithm composed of contrast adjustment and median filtering, thresholding and sobel operation, as pre-processing and post-processing. The result show that background and foreground regions are segmented in monumental inscription image.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.48 no.2
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• pp.11-23
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• 2011

In this paper, an accurate and fully automatic video object segmentation method is proposed for video conferencing systems in which the real-time performance is required. The proposed method consists of two steps: 1) accurate object extraction on the initial frame, 2) real-time object extraction from the next frame using the result of the first step. Object extraction on the initial frame starts with generating a cumulative edge map obtained from frame differences in the beginning. This is because we can estimate the initial shape of the foreground object from the cumulative motion. This estimated shape is used to assign the seeds for both object and background, which are needed for Graph-Cut segmentation. Once the foreground object is extracted by Graph-Cut segmentation, real-time object extraction is conducted using the extracted object and the double edge map obtained from the difference between two successive frames. Experimental results show that the proposed method is suitable for real-time processing even in VGA resolution videos contrary to previous methods, being a useful tool for immersive video conferencing systems.

• Journal of Korea Game Society
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• v.17 no.5
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• pp.113-122
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• 2017

The location of the objects that make up a game can be an element of immersion for players. repeatedly appearing at the same position, the fun may be reduced, and as the play time elapses, the players will feel the game's fun as they appear in a larger area than at the beginning of the game play. This paper is a study to find out the location of objects according to the passage of time and to see how players controlled these objects. First, foreground images are extracted and accumulated using OpenCV programming language. The accumulated result is displayed as a heat map image. Second, the mouse movement area is detected using the mouse tracking program and compared with the heat map image, so that the screen area in which the player is interested can be known.

• Journal of the Korea Society of Computer and Information
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• v.4 no.4
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• pp.34-39
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• 1999

In this paper, boundary extraction algorithm is suggested by removing boundary noises efficiently and simplifying object shape in binary image. To remove boundary noises, $2{times}2$ mask boundary extraction algorithm is modified . Proposed method is designed to generate a symmetric path for the parasitic branch noise and to analysis traced features on end point of noise. It can extract more simplified object boundary but preserve original object shape by combining white background color extraction result with foreground extraction result. The usefulness of the proposed method was proved through experiments with various binary images.

• 한국HCI학회:학술대회논문집
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• 2008.02a
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• pp.623-628
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• 2008

We present a new method of extracting foreground object from background image for vision-based game interface. Background Subtraction is an important preprocessing step for extracting the features of tracking objects. The image is divided into the cells where the Local Histogram with Gaussian kernel is computed and compared with the corresponding one using Bhattacharyya distance measure. The histogram-based method is partially robust against illumination change, noise and small moving objects in background. We propose a Multi-Scaled Integral Histogram approach for noise suppression and fast computation.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.01a
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• pp.63-66
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• 2009

Automatic segmentation of foreground from background in video sequences has attracted lots of attention in computer vision. This paper proposes a novel framework for the background subtraction that the foreground is segmented from the background by directly subtracting a background image from each frame. Most previous works focus on the extraction of more reliable seeds with threshold, because the errors are occurred by noise, weak color difference and so on. Our method has good segmentations from the approximate seeds by using the Random Walks with Restart (RWR). Experimental results with live videos demonstrate the relevance and accuracy of our algorithm.

• Journal of Advanced Information Technology and Convergence
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• v.9 no.2
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• pp.29-39
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• 2019

Tidal Flats are very important natural resource and various efforts have been made to protect it from environmental pollutions. The projects to monitor the environmental changes by periodically observing the creatures in tidal flats are underway. However, they are being done inefficiently by people directly observing. In this paper, we propose an object segmentation method that can be applied to the applications which automatically monitor the living creatures in tidal flats. In the proposed method, a foreground map representing the location of objects is obtained by using a temporal difference method, and then a superpixel method is applied to detect the detailed boundary of an object. The region of a crab is extracted finally by combining the foreground map and the superpixel information. Experimental results show that the proposed method separates crab regions from a tidal flat image easily and accurately.