• The Journal of the Korea institute of electronic communication sciences
• /
• v.6 no.3
• /
• pp.349-354
• /
• 2011

In this paper we propose a simple efficient stereo matching algorithm to recover sharp object boundaries and to obtain dense disparity map using new multiple line shape windows. To this end, we consider left-right consistency and unique constraint. From the experimental results it is found that the proposed algorithm is very good for obtaining sharp and dense disparity maps for stereo image pairs.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
• /
• 2003.05c
• /
• pp.194-199
• /
• 2003

Depth error correction effect for maladjusted stereo cameras with calibrated pixel distance parameter is presented. The proposed neural network technique is the real time computation method based theory of inter-node diffusion for searching the safety distances from the sudden appearance-objects during the work driving. The main steps of the distance computation using the theory of stereo vision like the eyes of man is following steps. One is the processing for finding the corresponding points of stereo images and the other is the interpolation processing of full image data from nonlinear image data of objects. All of them request much memory space and time. Therefore the most reliable neural-network algorithm is derived for real-time matching of objects, which is composed of a dynamic programming algorithm based on sequence matching techniques.

• Journal of Mechanical Science and Technology
• /
• v.17 no.10
• /
• pp.1411-1422
• /
• 2003

The detection of free spaces between obstacles in a scene is a prerequisite for navigation of a mobile robot. Especially for stereo vision-based navigation, the problem of correspondence between two images is well known to be of crucial importance. This paper describes multi-range approach of area-based stereo matching for grid mapping and visual navigation in uncertain environment. Camera calibration parameters are optimized by evolutionary algorithm for successful stereo matching. To obtain reliable disparity information from both images, stereo images are to be decomposed into three pairs of images with different resolution based on measurement of disparities. The advantage of multi-range approach is that we can get more reliable disparity in each defined range because disparities from high resolution image are used for farther object a while disparities from low resolution images are used for close objects. The reliable disparity map is combined through post-processing for rejecting incorrect disparity information from each disparity map. The real distance from a disparity image is converted into an occupancy grid representation of a mobile robot. We have investigated the possibility of multi-range approach for the detection of obstacles and visual mapping through various experiments.

• Journal of the Korean Society for Precision Engineering
• /
• v.19 no.5
• /
• pp.36-42
• /
• 2002

This paper presents the way of building an occupancy grid map which a mobile robot needs to autonomously navigate in the unknown environment. A disparity map resulting from stereo matching can be converted into the 2D distance information. If the stereo matching has some errors, however, the subsequent map becomes unreliable. In this paper, a new morphological filter is proposed to reject 'spikes' of the disparity map due to stereo mismatch by considering the fact that these spikes occur locally. The new method has advantages that it is simpler and more easily realized than existing similar algorithms. Several occupancy grid maps based on stereo vision using the proposed algorithm have been built and compared with the actual distance information to verify the validity of the proposed method.

• Korean Journal of Remote Sensing
• /
• v.18 no.2
• /
• pp.81-90
• /
• 2002

We carried out accuracy assessment for DEM extraction from the KOMPSAT-1 EOC stereo images over Daejeon and Nonsan in Korea. DEM generation divided into two parts. One is camera modeling and the other stereo matching. We used Orun & Natarajan's(1994) model and Gupta & Hartley's(1997) model in the camera modeling step and checked the possibility using Orun & Natarajan and Gupta & Hartley's models in EOC stereo pairs. For stereo matching, we used an algorithms developed in-house for SPOT images and showed that this algorithm could work with EOC images. Using these algorithms, DEMs were successfully generated from EOC images. The comparison of DEM from EOC Images with a DEM from SPOT Images showed that EOC could be used for high-accuracy DEM generation.

• Proceedings of the KIEE Conference
• /
• 2008.07a
• /
• pp.1843-1844
• /
• 2008

In this paper, the distance from the camera to the object is measured by using stereo camera. The stereo camera acquires two images which have a disparity from left and right camera. The disparity could be calculated by stereo matching of two images and using the disparity, the distance was calculated by triangular method. The distance estimation was carried out as widen the distance from the camera to the object with several operation methods of stereo matching. The result of experiment was under 10 percent error compared with the real distance. Therefore, by using this result, stereo camera would be adapt to the object tracking robot research or any other related area.

• Proceedings of the IEEK Conference
• /
• 2008.06a
• /
• pp.935-936
• /
• 2008

Usually stereo matching methods have some limitations in finding out matching points specially at the boundaries of objects This paper proposes a new method which reduces noises incurred in the process of determining disparity with our energy-based stereo matching method. Our method exploits segmentation results so that pixels within the intra-region have similar disparity values.

• Proceedings of the IEEK Conference
• /
• 2003.11a
• /
• pp.179-182
• /
• 2003

This paper proposes a new stereo matching algorithm using both the divide-and-conquer method and the DSI(Disparity Space Image) technique. Firstly, we find salient feature points on the each scanline of the left image and find the corresponding feature point at the right image. Then the problem of a scanline is divided into several subproblems. By this way, matching of the subintervals is implemented by using the DSI technique. The DSI technique for stereo matching process is a very efficient solution to find matches and occlusions simultaneously and it is very speedy. In addition, we apply three occluding patterns to process occluded regions, as a result, we reduce mismatches at the disparity discontinuity.

• Proceedings of the Korean Society of Broadcast Engineers Conference
• /
• 2009.01a
• /
• pp.99-102
• /
• 2009

In this paper a hierarchical stereo matching algorithm based on feature extraction is proposed. The boundary (edge) as feature point in an image is first obtained by segmenting an image into red, green, blue and white regions. With the obtained boundary information, disparities are extracted by matching window on the image boundary, and the initial disparity map is generated when assigned the same disparity to neighbor pixels. The final disparity map is created with the initial disparity. The regions with the same initial disparity are classified into the regions with the same color and we search the disparity again in each region with the same color by changing block size and search range. The experiment results are evaluated on the Middlebury data set and it show that the proposed algorithm performed better than a phase based algorithm in the sense that only about 14% of the disparities for the entire image are inaccurate in the final disparity map. Furthermore, it was verified that the boundary of each region with the same disparity was clearly distinguished.

• Proceedings of the Korean Society of Broadcast Engineers Conference
• /
• 2012.11a
• /
• pp.52-53
• /
• 2012

Belief propagation (BP) is a commonly used global energy minimization algorithm for solving stereo matching problem in 3D reconstruction. However, it requires large memory bandwidth and data size. In this paper, we propose a novel memory-efficient algorithm of BP in stereo matching on the Graphics Processing Units (GPU). The data size and transfer bandwidth are significantly reduced by storing only a part of the whole message. In order to maintain the accuracy of the matching result, the local messages are reconstructed using shared memory available in GPU. Experimental result shows that there is almost an order of reduction in the global memory consumption, and 21 to 46% saving in memory bandwidth when compared to the conventional algorithm. The implementation result on a recent GPU shows that we can obtain 22.8 times speedup in execution time compared to the execution on CPU.