• The Journal of Korean Institute of Communications and Information Sciences
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• v.24 no.9B
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• pp.1704-1712
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• 1999

This research features efficient detection of obstacles, especially vehicles, in the forward direction of navigation for the development of unmanned automous vehicle. We separate image regions into ground and non-ground planes using the Helmholtz shearing technique in order to reliably exclude regions that do not contain obstacles. We propose a computationally simple and efficient method for the detection of vehicles in the forward direction by analysis of horizontally and vertically projected histograms of residual disparity map obtained from Helmholtz shearing. We have experimented the proposed method on real outdoor stereo data. Experimental results show that our method gives accurate detection of forward vehicles and is computationally very efficient.

• The Journal of Engineering Research
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• v.6 no.2
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• pp.99-107
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• 2004

In stereo matching system, it is efficient using segment patch, which divides the image into homogeneous region in color or similar intensity, because it preserves the disparity boundary and disparity continuity in low textured region. But many miss matching occur in the highly textured region because of the over segmentation that makes patch small and ambiguous. In this paper, in order to solve problems, we propose adaptive patch matching based on the watershed image segmentation. Performance was verified in experimental results.

• The KIPS Transactions:PartA
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• v.14A no.5
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• pp.301-308
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• 2007

This paper proposes high performance coprocessor architecture for real time dense disparity computation based on a phase-based binocular stereo matching technique called local weighted phase-correlation(LWPC). The algorithm combines the robustness of wavelet based phase difference methods and the basic control strategy of phase correlation methods, which consists of 4 stages. For parallel and efficient hardware implementation, the proposed architecture employs SIMD(Single Instruction Multiple Data Stream) architecture for each functional stage and all stages work on pipelined mode. Such that the newly devised pipelined linear array processor is optimized for the case of row-column image processing eliminating the need for transposed memory while preserving generality and high throughput. The proposed architecture is implemented with Xilinx HDL tool and the required hardware resources are calculated in terms of look up tables, flip flops, slices, and the amount of memory. The result shows the possibility that the proposed architecture can be integrated into one chip while maintaining the processing speed at video rate.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.47 no.6
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• pp.86-96
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• 2010

In this paper, we propose stereo vision-based obstacle detection and vehicle verification methods using U-disparity map and bird's-eye view mapping. First, we extract a road feature using maximum frequent values in each row and column. And we extract obstacle areas on the road using the extracted road feature. To extract obstacle areas exactly we utilize U-disparity map. We can extract obstacle areas exactly on the U-disparity map using threshold value which consists of disparity value and camera parameter. But there are still multiple obstacles in the extracted obstacle areas. Thus, we perform another processing, namely segmentation. We convert the extracted obstacle areas into a bird's-eye view using camera modeling and parameters. We can segment obstacle areas on the bird's-eye view robustly because obstacles are represented on it according to ranges. Finally, we verify the obstacles whether those are vehicles or not using various vehicle features, namely road contacting, constant horizontal length, aspect ratio and texture information. We conduct experiments to prove the performance of our proposed algorithms in real traffic situations.

• ETRI Journal
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• v.26 no.6
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• pp.597-604
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• 2004

In stereoscopic television, there is a trade-off between visual comfort and 3-dimensional (3D) impact with respect to the baseline-stretch of a 3DTV camera. It is necessary to adjust the baseline-stretch at an appropriate the distance depending on the contents of a scene if we want to obtain a subjectively optimal quality of an image. However, it is very hard to obtain a small baseline-stretch using commercially available cameras of broadcasting quality where the sizes of the lens and CCD module are large. In order to overcome this limitation, we attempt to freely control the baseline-stretch of a stereoscopic camera by synthesizing the virtual views at the desired location of interval between two cameras. This proposed technique is based on the stereo matching and view synthesis techniques. We first obtain a dense disparity map using a hierarchical stereo matching with the edge-adaptive multiple shifted windows. Then, we synthesize the virtual views using the disparity map. Simulation results with various stereoscopic images demonstrate the effectiveness of the proposed technique.

• Journal of Advanced Navigation Technology
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• v.6 no.1
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• pp.27-36
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• 2002

As the number of autonomous vehicles is increased, drivers are trending toward constant interests in detecting distance between vehicles in close-range and maintaining the distance between forward and backward vehicles for drivers' safety. In this paper, we propose a method of detecting the distance between two vehicles by computing the disparity of the close-rang vehicle using stereo vision. The boundary of the vehicle is obtained by using the modified wavelet transform which has multi-resolution characteristics. Then the disparity between left and right images is computed using coarse-to-fine method and histogram matching. Here we transform the left-right stereo images through 3-steps using the modified wavelet for maintaining the original resolution. An experimental result showed that the proposed method had 4.65% in total error rate.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.25 no.3
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• pp.461-469
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• 2001

Existing area-based stereo algorithms rely heavily on rectangular windows for computing correspondence. While the algorithms with the rectangular windows are efficient, they generate relatively large matching errors due to variations of disparity profiles near depth discontinuities and doesnt take into account local deformations of the windows due to projective distortion. In this paper, in order to deal with these problems, a new correlation function with 4 directional line masks, based on robust estimator, is proposed for the selection of potential matching points. These points is selected to consider depth discontinuities and reduce effects on outliers. The proposed matching method finds an arbitrarily-shaped variable window around a pixel in the 3d array which is constructed with the selected matching points. In addition, the method take into account the local deformation of the variable window with a constant disparity, and perform the estimation of sub-pixel disparities. Experiments with various synthetic images show that the proposed technique significantly reduces matching errors both in the vicinity of depth discontinuities and in continuously smooth areas, and also does not be affected drastically due to outlier and noise.

• Journal of the Korean Institute of Telematics and Electronics
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• v.27 no.3
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• pp.116-123
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• 1990

Most algorithms utilized the horizontal epipolar lines for solving the correspondence problem in 3-D computer vision. However, the requirement is very difficult to be satisfied in real situations. In this paper, we propose a binocular-stereo matching algorithm, based on line matching method, which does not require the horizontal epipolar lines of the extreme pixels of a given line segment and two circles whose radius is equal to the maximum disparity. And we use the features including the direction of line segments, edge strength and cross-correlation for line matching. The experimental results show that the proposed algorithm can be a useful tool for solving the correspondence problem in 3-D computer vision.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.31B no.8
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• pp.74-86
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• 1994

In this paper a hierarchical stereo matching algorithm to obtain the disparity in wavelet transformed domain by using locally adaptive window and weights is proposed. The pyramidal structure obtained by wavelet transform is used to solve the loss of information which the conventional Gaussian or Laplacian pyramid have. The wavelet transformed images are decomposed into the blurred image the horizontal edges the vertical edges and the diagonal edges. The similarity between each wavelet channel of left and right image determines the relative importance of each primitive and make the algorithm perform the area-based and feature-based matching adaptively. The wavelet transform can extract the features that have the dense resolution as well as can avoid the duplication or loss of information. Meanwhile the variable window that needs to obtain precise and stable estimation of correspondense is decided adaptively from the disparities estimated in coarse resolution and LL(low-low) channel of wavelet transformed stereo image. Also a new relaxation algorithm that can reduce the false match without the blurring of the disparity edge is proposed. The experimental results for various images show that the proposed algorithm has good perfpormance even if the images used in experiments have the unfavorable conditions.

• Journal of Korea Society of Digital Industry and Information Management
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• v.8 no.3
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• pp.97-124
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• 2012

This paper analyzes qualitatively the stereo 3D content factors causing viewer's discomfort. For this, we perform a subjective test that each subject strokes a specific key whenever he (she) feels discomfort during watching a stereo 3D contents. Also we extract the data for the factors in the 3D contents to obtain their quantitative values and the amounts of the temporal changes. Those two sets of data are used to analyze the contents to find the factors which cause viewer's discomfort. The factors to be considered are the amount and the frequency of the disparity changes, story of the contents, situation or environments of a scene, movement and the position of the camera, color and luminance information as well as disparities themselves. We analyse the various strong and weak factors and their composites to find how much discomfort each factor or composite causes. We also show the situations and their related factors that causes less discomfort than the amount of their disparities.