• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.3
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• pp.407-415
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• 2012

In this paper, we propose a new stereo matching algorithm by using color information especially for stereo images containing human beings in the applications such as tele-presence system. In the proposed algorithm, we first remove the background regions by using a threshold value for stereo images obtained by stereo camera and then find an initial disparity map and segment a given image into R, G, B and white color components. We also obtain edges in the segmented image and estimate the disparity from the extract boundary regions. Finally, we generate the final disparity map by properly combining the disparity map of each color component. Experiment results show better performance compared with the window based method and the dynamic programing method especially for stereo images with human being.

• IEMEK Journal of Embedded Systems and Applications
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• v.3 no.2
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• pp.109-118
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• 2008

We present a robust localization algorithm using particle filter for mobile robots in a dynamic environment. It is difficult to describe moving obstacles like people or other robots on the map and the environment is changed after mapping. A mobile robot cannot estimate its pose robustly with this incomplete map because sensor observations are corrupted by un-modeled obstacles. The proposed algorithms provide robustness in such a dynamic environment by suppressing the effect of corrupted sensor observations with a selective update or a sampling from non-corrupted window. A selective update method makes some particles keep track of the robot, not affected by the corrupted observation. In a sampling from non-corrupted window method, particles are always sampled from several particle sets which use only non-corrupted observation. The robustness of proposed algorithm is validated with experiments and simulations.

• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.580-583
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• 2007

Various matching methods have been introduced by investigators to improve digital elevation model (DEM) accuracy of satellite imagery. This study proposed an area-based matching method according to land cover property using correlation coefficient of pixel brightness value between the two images for DEM generation from IKONOS stereo imagery. For this, matching line (where "matching line" implies straight line that is approximated to complex nonlinear epipolar geometry) is established by exterior orientation parameters to minimize search area. The matching is carried out based on this line. Land cover classes are divided off into water, urban land, forest and agricultural land. Matching size is selected using a correlation-coefficient image in the four areas. The selected sizes are $81{\times}81$ pixels window, $21{\times}21$ pixels window, $119{\times}119$ pixels window and $51{\times}51$ pixels window in the water area, urban land, forest land and agricultural land, respectively. And hence, DEM is generated from IKONOS stereo imagery using the selected matching sizes and land cover map on the four types.

• Journal of information and communication convergence engineering
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• v.6 no.3
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• pp.343-347
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• 2008

Wakeup schemes that turn off sensors' radio when communication is not necessary have great potential in energy saving. At the start of each beacon interval in the IEEE 802.11 power saving mode specified for DCF, each node periodically wakes up for duration called the ATIM Window. However, in the power saving mechanism specified in IEEE 802.11, all nodes use the same ATIM window size. Since the ATIM window size critically affects throughput and energy consumption, a fixed ATIM window does not perform well in all situations. This paper proposes an adaptive mechanism to dynamically choose an ATIM window size according to network condition. Simulation results show that the proposed scheme outperforms the IEEE 802.11 power saving mechanism in terms of the amount of power consumed and the packet delivery ratio.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.52 no.3
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• pp.163-172
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• 2003

A stereo matching has been an important tool for the reconstruction of 3D terrain. The current state of stereo matching technology has reached the level where a very elaborate DEM(Digital Elevation Map) can be obtained. However, there still exist many factors causing DEM error in stereo matching. This paper propose a new method to reduce the error caused by the lack of significant features in the correlation window The proposed algorithm keeps the correlation window as small as possible, as long as there is a significant feature in the window. Experimental results indicate that the proposed method increases the DEM accuracy by $72.65\%$ in the plain area and $41.96\%$ in the mountain area over the conventional scheme. Comparisons with Kanade's result show that the proposed method eliminates spike type of errors more efficiently than Kanade's adaptive window technique and produces reliable DEM.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.12
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• pp.46-54
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• 2015

SAR is a Radar to obtain the video information using a radio wave. Platform emit the radio wave, depending backscattered waves returned from the target object the signal to the distance, to create a topographical map is recorded in two-dimensional image. In this paper, through a simulation to apply a variety of window in the SAR image processing for SAR image recovery is to study the application effect of the window, as a result, at the side of the signal of the SNR, Flattop window to improve the best performance it was confirmed to show.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 1997.06a
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• pp.131-136
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• 1997

We present a method to estimate a dense and sharp depth map using multiple cameras for the application to flexible video production. A key issue for obtaining sharp depth map is how to overcome the harmful influence of occlusion. Thus, we first propose to selectively use the depth information from multiple cameras. With a simple sort and discard technique, we resolve the occlusion problem considerably at a slight sacrifice of noise tolerance. However, boundary overreach of more textured area to less textured area at object boundaries still remains to be solved. We observed that the amount of boundary overreach is less than half the size of the matching window and, unlike usual stereo matching, the boundary overreach with the proposed occlusion-overcoming method shows very abrupt transition. Based on these observations, we propose a hierarchical estimation scheme that attempts to reduce boundary overreach such that edges of the depth map coincide with object boundaries on the one hand, and to reduce noisy estimates due to insufficient size of matching window on the other hand. We show the hierarchical method can produce a sharp depth map for a variety of images.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2000.11a
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• pp.666-669
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• 2000

Localization is the process of aligning the robot's local coordinates with the global coordinates of a map. A mobile robot's location is basically computed by a dead reckoning scheme, but this position information becomes increasingly inaccurate during navigation due to odometry errors. In this paper, the method of building a map of a robot's environment using ultrasonic sensor data and the occupancy grid map scheme is briefly presented. Then, the search and matching algorithms to compensate for the odometry error by comparing the local map with the reference map are proposed and verified by experiments. It is shown that the compensated error is not accumulated and exists within the limited range.

• Proceedings of the Korean Information Science Society Conference
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• 2004.04b
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• pp.808-810
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• 2004

본 논문에서는 Contrast map과 Salient point를 이용하여 영상에서 중요한 객체를 자동으로 추출하는 방법을 제안한다. 우선 인간의 시각 체계와 유사한 밝기(luminance), 색상(color) 그리고 방향성(orientation) 3가지의 특징정보를 이용하여 각각의 특징정보로부터 feature map을 생성하고 이 3가지의 feature map을 선형 결합하여 contrast map을 생성한다. 이렇게 생성된 하나의 contrast map을 이용하여 대략적인 Attention Window (AW)의 위치를 결정한다. 다음으로, 영상으로부터 웨이블릿 변환을 적용하여 salient point를 찾고, salient point의 분포와 contrast map의 중요도에 따라 AW의 크기를 실제 중요 객체의 크기와 가장 유사하도록 축소시킨다. 이렇게 선택되고 축소된 AW안에서 실제 중요 객체를 추출하기 위해 AW 내부에 존재하는 영상에 대해서만 영상 분할을 하고 불필요한 영역을 제거하여 자동으로 중요객체를 추출하도록 한다.

• Journal of the Semiconductor & Display Technology
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• v.8 no.4
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• pp.95-100
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• 2009

This paper presents an efficient disparity matching, using sum of absolute difference (SAD) and dynamic programming (DP) algorithm. This algorithm makes use of one of area-based algorithm which is the absolute sum of the pixel difference corresponding to the window size. We use the information of the right eye brightness (B) and the left eye brightness to get an best matching results and apply the results to the left eye image using the window go by the brightness of the right eye image. This is that we can control the brightness. The major feature of this algorithm called SAD+DP+B is that although Root Mean Square (RMS) performance is slightly less than SAD+DP, due to comparing original image, its visual performance is increased drastically for matching the disparity map on account of its matching compared to SAD+DP. The simulation results demonstrate that the visual performance can be increased and the RMS is competitive with or slightly higher than SAD+DP.