• Korean Journal of Remote Sensing
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• v.21 no.3
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• pp.229-242
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• 2005

Photogrammetry is a current method of GIS data acquisition. However, as a matter of fact, a large manpower and expenditure for making detailed 3D spatial information is required especially in urban areas where various buildings exist. There are no photogrammetric systems which can automate a process of spatial information acquisition completely. On the other hand, LiDAR has high potential of automating 3D spatial data acquisition because it can directly measure 3D coordinates of objects, but it is rather difficult to recognize the object with only LiDAR data, for its low resolution at this moment. With this background, we believe that it is very advantageous to integrate LiDAR data and stereo CCD images for more efficient and automated acquisition of the 3D spatial data with higher resolution. In this research, the automatic urban object recognition methodology was proposed by integrating ultra highresolution stereo images and LiDAR data. Moreover, a method to enable more reliable and detailed stereo matching method for CCD images was examined by using LiDAR data as an initial 3D data to determine the search range and to detect possibility of occlusions. Finally, intellectual DSMs, which were identified urban features with high resolution, were generated with high speed processing.

• Korean Journal of Remote Sensing
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• v.21 no.5
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• pp.383-392
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• 2005

Vegetation classes, especially grass and tree classes, are often confused in classification when conventional spectral pattern recognition techniques are used to classify urban areas. This paper reports on a study to improve the classification results by using an automated process of considering height information in separating urban vegetation classes, specifically tree and grass, using three-band, high-spatial resolution, digital aerial imagery. Height information was derived photogrammetrically from stereo pair imagery using cross correlation image matching to estimate differential parallax for vegetation pixels. A threshold value of differential parallax was used to assess whether the original class was correct. The average increase in overall accuracy for three test stereo pairs was $7.8\%$, and detailed examination showed that pixels reclassified as grass improved the overall accuracy more than pixels reclassified as tree. Visual examination and statistical accuracy assessment of four test areas showed improvement in vegetation classification with the increase in accuracy ranging from $3.7\%\;to\;18.1\%$. Vegetation classification can, in fact, be improved by adding height information to the classification procedure.

• Korean Journal of Remote Sensing
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• v.23 no.2
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• pp.113-117
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• 2007

In this paper, we propose a new method for determining automatically the size of the matching window using histogram of the gradient in order to improve the performance of stereo matching using one-meter resolution satellite imagery. For each pixel, we generate Flatness Index Image by calculating the mean value of the vertical or horizontal intensity gradients of the 4-neighbors of every pixel in the entire image. The edge pixel has high flatness index value, while the non-edge pixel has low flatness index value. By using the histogram of the Flatness Index Image, we find a flatness threshold value to determine whether a pixel is edge pixel or non-edge pixel. If a pixel has higher flatness index value than the flatness threshold value, we classify the pixel into edge pixel, otherwise we classify the pixel into non-edge pixel. If the ratio of the number of non-edge pixels in initial matching window is low, then we consider the pixel to be in homogeneous region and enlarge the size of the matching window We repeat this process until the size of matching window reaches to a maximum size. In the experiment, we used IKONOS satellite stereo imagery and obtained more improved matching results than the matching method using fixed matching window size.

• Journal of Institute of Control, Robotics and Systems
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• v.9 no.11
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• pp.899-905
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• 2003

An intermediate images generation method using multi-resolution based hierarchical block matching disparity map is proposed. This method is composed of a disparity estimation, an occlusion detection and intermediate image synthesis. For the disparity estimation, which is one of the important processes in intermediate image synthesis, we use the multi-resolution based hierarchical block matching algorithm to overcome the imperfect ness of block matching algorithm. The proposed method makes disparity maps more accurate and dense by multi-resolution based hierarchical block matching, and the estimated disparity maps are used to generate intermediate images of stereo images. Generated intermediate images show 0.1∼1.4 ㏈ higher PSNR than the images obtained by block matching algorithm.

• Korean Journal of Remote Sensing
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• v.27 no.1
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• pp.51-58
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• 2011

Accurate DEM(Digital Elevation Model) generation using satellite images is an active research topic. This paper focuses on generation of a DEM with multiple Kompsat-2 images. For DEM generation, we applied an orbit-attitude sensor model and a RPM sensor model to stereo and multiple Kompsat-2 images respectively. For matching, we used an object-space based matching method. Through the result of this experiment, we could confirm that the sensor model from multiple images is more accurate than the model from stereo images. Also DEM from multiple images gave much better performance than DEM from stereo images.

• The KIPS Transactions:PartB
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• v.9B no.2
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• pp.237-244
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• 2002

In this paper, we propose a stereo image recognition-based method for measuring the volume of the rectangular parallelepiped. The method measures the volume from two images captured with two CCD (charge coupled device) cameras by sequential processes such as ROI (region of interest) extraction, feature extraction, and stereo matching-based vortex recognition. The proposed method makes it possible to measure the volume of the 3D object at high speed because only a few features are used in the process of stereo matching. From experimental results, it is demonstrated that this method is very effective for measuring the volume of the rectangular parallelepiped at high speed.

• Journal of Internet Computing and Services
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• v.10 no.4
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• pp.25-33
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• 2009

In the paper, we proposed a new system to retrieve 3D wrinkle data based on stereo images. Usually, 3D reconstruction based on stereo images or video is very popular and it is the research focus, which has been applied for culture heritage, building and other scene. The target is object measurement, the scene depth calculation and 3D data obtained. There are several challenges in our research. First, it is hard to take the full information wrinkle images by cameras because of light influence, skin with non-rigid object and camera performance. We design a particular computer vision system to take winkle images with a long length camera lens. Second, it is difficult to get the dense stereo data because of the hard skin texture image segmentation and corner detection. We focus on semi-dense stereo matching algorithm for the wrinkle depth. Compared with the 3D scanner, our system is much cheaper and compared with the physical modeling based method, our system is more flexible with high performance.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.16 no.2
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• pp.177-185
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• 1998

There is an increasing request for 3D data and outlines on building for urban planning and design. This paper describes an approach to extract building using Digital Surface Models(DSM) and stereo pairs of aerial images. DSM contain informations not only about the topographic surface like Digital Elevation Models(DEM), but also about buildings and other objects higher than the surrounding topographic surface, e.g. tees. We therefore describe our approach consisting of two step procedures. The first step of the approach is to generate DSM by stereo matching using Maximum Likelihood Estimation and Dynamic Programming. The proposed stereo matching is using the cost function for finding the disparity between the left and right image, and the Dynamic Programming for solving the stereo matching problem. The second step is to detect building outlines using the DSM and the edge informations extracted from a digital aerial image by Sobel Operator. The overlay analysis of the DSM and the edge information by Sobel Operator was efficient to detect building outlines.

• Journal of Institute of Control, Robotics and Systems
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• v.8 no.10
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• pp.874-880
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• 2002

A number of techniques have been proposed for 3D display using view-difference of two eyes. These methods do not express enough reality like real world. The display images have to change according to the position of a viewer to improve reality. In this paper, we present an approach for generating intermediate image between two different view images by applying new image interpolation algorithm The interpolation algorithm is designed to cope with complex shapes. The proposed image interpolation algorithm generates rotated image about vertical axes by any angle from base images. Each base image that was obtained from CCD camera has an view-angle difference of $3^{\circ}C$, $5.5^{\circ}C$, $^{\circ}C$, $22^{\circ}C$, and $45^{\circ}C$. The proposed into mediate image generation method uses the geometric analysis of image and depth information through the block-based matching method.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.53 no.7
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• pp.509-516
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• 2004

This paper proposes an image processing algorithm for detecting obstacles on road using DLI(disparity of lane-related information) that is generated by stereo images acquired from dual cameras mounted on a moving vehicle. The DLI is a disparity that is acquired using a single lane information from road lane detection. For the purpose to reduce processing time, we use small block of edge-histogram based blocking logic. This algorithm detects moving objects such as preceding vehicles and obstacles. The proposed algorithm has been implemented in a personal computer with the road image data of a typical highway. We successfully performed experiments under a wide variety of road conditions without changing parameter values or adding human intervention. Experimental results also showed that the proposed DLI is quite successful.