• Proceedings of the KSME Conference
• /
• 2003.11a
• /
• pp.658-663
• /
• 2003

A process of 3-D stereo particle image velocimetry(PIV)was developed for the measurement of an illuminated sliced section field of 3-D complex flows. The present method includes modeling of camera by a calibrator based on the homogeneous coordinate system, transformation of the oblique-angled image to the right-angled image, identification of 2-D velocity vectors by 2-D cross-correlation equation, stereo matching of 2-D velocity vectors of two cameras, accurate calculation of 3-D velocity vectors by homogeneous coordinate system, removal of error vectors by a statistical method followed by a continuity equation criteria, and finally 3-D display as the post processing. An experimental system was also used for the application of the proposed method. Two high speed digital CCD cameras and an Argon-Ion Laser for the illumination were adopted to clarify the time-dependent characteristics of the leading edge extension(LEX) in a highly swept shape applied to a delta wing found in modern air-fighters.

• The KIPS Transactions:PartB
• /
• v.15B no.4
• /
• pp.269-274
• /
• 2008

In this paper, we propose a new stereo correspondence method for generating excellent external energy for snake-based object segmentation methods in stereo images. Our method first generates an edge-based disparity map by performing stereo correspondence between multi-level edge maps of the stereo image pair. Only edges of similar strength are considered for matching. To filter the disparity map for edges of the object of interest, the method estimates the object's disparity value by matching the pattern of edges of the region of interest in the left image against candidate patterns in the right image. The filtered edge map is then used to generate external energy for the snake. The proposed method has been tested on two snake models and results show a noticeable enhancement on performance of the snake when compared with other methods.

• 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.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.37 no.5
• /
• pp.315-322
• /
• 2019

DSM (Digital Surface Model) is a digital representation of ground surface topography or terrain that is widely used for hydrology, slope analysis, and urban planning. Aerial photogrammetry and LiDAR (Light Detection And Ranging) are main technology for urban DSM generation but high-resolution satellite imagery is the only ingredient for remote inaccessible areas. Traditional automated DSM generation method is based on correlation-based methods but recent study shows that a modern pixelwise image matching method, SGM (Semi-Global Matching) can be an alternative. Therefore this study investigated the application of SGM for Kompsat satellite data of KARI (Korea Aerospace Research Institute). Firstly, the sensor modeling was carried out for precise ground-to-image computation, followed by the epipolar image resampling for efficient stereo processing. Secondly, SGM was applied using different parameterizations. The generated DSM was evaluated with a reference DSM generated by the first pulse returns of the LIDAR reference dataset.

• Transactions of the Korean Society of Mechanical Engineers A
• /
• v.21 no.10
• /
• pp.1551-1560
• /
• 1997

This study is devoted to the detection of the 3-dimensional point obstacles on the plane by using accumulated scan line images. The proposed accumulating only one scan line allow to process image at real time. And the change of motion of the feature in image is small because of the short time between image frames, so it does not take much time to track features. To obtain recursive optimal obstacles position and robot motion along to the motion of camera, Kalman filter algorithm is used. After using Kalman filter in case of the fixed environment, 3-dimensional obstacles point map is obtained. The position and motion of moving obstacles can also be obtained by pre-segmentation. Finally, to solve the stereo ambiguity problem from multiple matches, the camera motion is actively used to discard mis-matched features. To get relative distance of obstacles from camera, parallel stereo camera setup is used. In order to evaluate the proposed algorithm, experiments are carried out by a small test vehicle.

• The KIPS Transactions:PartB
• /
• v.17B no.1
• /
• pp.63-68
• /
• 2010

In this paper, we propose a multiresolution stereo matching method based on genetic algorithm using edge information. The proposed approach considers the matching environment as an optimization problem and finds the solution by using a genetic algorithm. A cost function composes of certain constraints which are commonly used in stereo matching. We defines the structure of chromosomes using edge pixel information of reference image of stereo pair. To increase the efficiency of process, we apply image pyramid method to stereo matching and calculate the initial disparity map at the coarsest resolution. Then initial disparity map is propagated to the next finer resolution, interpolated and performed disparity refinement. We valid our approach not only reduce the search time for correspondence but alse ensure the validity of matching.

• 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 Korea Institute of Information and Communication Engineering
• /
• v.20 no.10
• /
• pp.2001-2006
• /
• 2016

The stereo radiation detection system detects the gamma source and acquires two dimensional left and right images for gamma source and visible objects using the detection result. And then the system measures the distance to the radiation source from the system in 3D space using stereo vision algorithm. In this paper, we implemented the fast detection algorithm for gamma source from the system in 3D space to reduce the detection time with image processing algorithms. Additionally, the system's performance is verified through experiments on gamma irradiation facilities. As a result, if the fast detection algorithm applied to the system, we can confirm that the detection system represents a 35% better performance than the conventional detection method that is full scanning to acquire the stereo image. We also have visualized a gamma source distribution through a 3D monitor using the stereo vision algorithm in order to provide the information of radiation spatial distribution to the user efficiently.

• International Journal of Highway Engineering
• /
• v.15 no.5
• /
• pp.177-185
• /
• 2013

PURPOSES : This study attempts to design and establish the road surface condition detection system by using the image processing that is expected to help implement the low-cost and high-efficiency road information detection system by examining technology trends in the field of road surface condition information detection and related case studies. METHODS : Adapted visual information collecting method(setting a stereo camera outside of the vehicle) and visual information algorithm(transform a Wavelet Transform, using the K-means clustering) Experiments and Analysis on Real-road, just as four states(Dry, Wet, Snow, Ice). RESULTS : Test results showed that detection rate of 95% or more was found under the wet road surface, and the detection rate of 85% or more in snowy road surface. However, the low detection rate of 30% was found under the icy road surface. CONCLUSIONS : As a method to improve the detection rate of the mobile road surface condition information detection system developed in this study, more accurate phase analysis in the image processing process was needed. If periodic synchronization through automatic settings of the camera according to weather or ambient light was not made at the time of image acquisition, a significant change in the values of polarization coefficients occurs.

• Journal of Broadcast Engineering
• /
• v.18 no.3
• /
• pp.362-371
• /
• 2013

This paper presents a framework of real-time augmented reality on 3-D mobile display with stereo camera tracking. In the framework, camera poses are jointly estimated with the geometric relationship between stereoscopic images, which is based on model-based tracking. With the estimated camera poses, the virtual contents are correctly augmented on stereoscopic images through image rectification. For real-time performance, stereo camera tracking and image rectification are efficiently performed using multiple threads. Image rectification and color conversion are accelerated with a GPU processing. The proposed framework is tested and demonstrated on a commercial smartphone, which is equipped with a stereoscopic camera and a parallax barrier 3-D display.