• The Journal of Korean Institute of Communications and Information Sciences
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• v.27 no.2A
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• pp.137-145
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• 2002

In the method of 3D modeling, stereo matching method which obtains three dimensional depth information from the two images is taken from the different view points. In general, it is very essential work for the 3D modeling from 2D stereo images to estimate the exact disparity through fading the conjugate pair of pixel from the left and right image. In this paper to solve the problems of the stereo image disparity estimation, we introduce a novel approach method to improve the exactness and efficiency of the disparity. In the first place, we perform a wavelet transformation of the stereo images and set the reference points in the image by the feature-based matching method. This reference points have very high probability over 95 %. In the base of these reference points we can decide the size of the variable block searching windows for estimating dense disparity of area based method and perform the ordering constraint to prevent mismatching. By doing this, we could estimate the disparity in a short time and solve the occlusion caused by applying the fried-sized windows and probable error caused by repeating patterns.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.27 no.1
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• pp.667-675
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• 2009

Image matching is widely applied in image application areas, such as remote sensing and GIS. In general, the initial set of matching points always includes outlier which affect the accuracy of image matching. The purpose of this paper is to develop a robust approach for outlier detection and removal in order to keep accuracy in image matching applications. In this paper we use three automatic outlier detection techniques of backward matching and affine transformation, and RANSAC(RANdom SAmple Consensus) algorithm. Moreover, we calculate overlapping apply and steps block-based processing for fast and efficient image matching in pre-processing steps. The suggested approach in this paper has been applied to real frame image pairs and the results have been analyzed in terms of the robustness and the efficiency.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.40 no.4
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• pp.437-444
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• 2020

A lunar rover's optical camera is used to provide navigation and terrain information in an exploration zone. However, due to the scant presence of atmosphere, the Moon has homogeneous terrain with dark soil. Also, in extreme environments, the rover has limited data storage with low computation capability. Thus, for successful exploration, it is required to examine feature detection and matching methods which are robust to lunar terrain and environmental characteristics. In this research, SIFT, SURF, BRISK, ORB, and AKAZE are comparatively analyzed with lunar terrain images from a lunar rover. Experimental results show that SIFT and AKAZE are most robust for lunar terrain characteristics. AKAZE detects less quantity of feature points than SIFT, but feature points are detected and matched with high precision and the least computational cost. AKAZE is adequate for fast and accurate navigation information. Although SIFT has the highest computational cost, the largest quantity of feature points are stably detected and matched. The rover periodically sends terrain images to Earth. Thus, SIFT is suitable for global 3D terrain map construction in that a large amount of terrain images can be processed on Earth. Study results are expected to provide a guideline to utilize feature detection and matching methods for future lunar exploration rovers.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.5
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• pp.960-966
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• 2017

In this paper, we proposed an algorithm that can extract lesion by inputting a medical image. Feature points are extracted using SIFT algorithm to extract genetic training of medical image. To increase the intensity of the feature points, the input image and that raining image are matched using vector similarity and the lesion is extracted. The vector similarity match can quickly lead to lesions. Since the direction vector is generated from the local feature point pair, the direction itself only shows the local feature, but it has the advantage of comparing the similarity between the other vectors existing between the two images and expanding to the global feature. The experimental results show that the lesion matching error rate is 1.02% and the processing speed is improved by about 40% compared to the case of not using the feature point intensity information.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1995.04b
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• pp.400-407
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• 1995

The straightness property is one of fundamental geometric tolerances to be strictly controlled for guideways of machine tools and measuring machines. The staightness measurement for long guideways was usually difficult to perform, and it needed additional equipments or special treatment with limited application. In this paper, a new approach is proposed using the profile matching technique for the long guideways, which can be applicable to most of straghtness measurements. An edge of relativelly sthort length is located along a divided section of a long guideway, and the local straightness measurement is performed. The edge is then moved to the next section with several positions overlap. After thelocal straightness profile is measured for every section along the long guideway with overlap, the global straightness profile is constructed using the profile matching technique based on theleast squares method. The proposed techinique is numerically tested for two cases of known global straightness profile arc profile and irregular profile and those profiles with and without random error intervention, respectively. When norandom errors are involved, the constructed golval profile is identical to the original profile. When the random errors are involved, the effect of the number of overlap points are investigated, and it is also found that the difference between the difference between the constructed and original profiles is very close to the limit of random uncertainty with juist few overlap points. The developed technique has been practically applied to a vertical milling machine of moving table type, and showed good performance. Thus the accuracy and efficiency of the proposed method are demonstrated, and shows great potential for variety of application for most of straightness measuirement cases using straight edges, laser optics, and angular measurement equipments.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.25 no.4
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• pp.279-287
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• 2007

The increased availability of portable, low-cost, high resolution video equipments have resulted in a rapid growth of the applications for video sequences. These video devices can be mounted in handhold unit, mobile unit and airborne platforms like maned or unmaned helicopter, plane, airship, etc. This paper describes the feasibility fur generating image map from the experimental results we designed to track the interested points extracted by KLT operator in the neighboring frames and implement image matching for each frames taken from UAV (Unmaned Aerial Vehicle). In the image registration for neighbourhood frames of aerial video, the results demonstrate the successful rate of matching slightly decreases as the drift between frames increases, and also that the stable photographing is more important matching condition than the pixel shift.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.4
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• pp.164-174
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• 2015

In a real scenario, radiometric change has frequently occurred in the stereo image acquisition process using multiple cameras with geometric characteristics or moving a single camera because it has different camera parameters and illumination change. Conventional stereo matching algorithms have a difficulty in finding correct corresponding points because it is assumed that corresponding pixels have similar color values. In this paper, we present a new method based on the local descriptor reflecting intensity, gradient and texture information. Furthermore, an adaptive weight for local descriptor based on the entropy is applied to estimate correct corresponding points under radiometric variation. The proposed method is tested on Middlebury datasets with radiometric changes, and compared with state-of-the-art algorithms. Experimental result shows that the proposed scheme outperforms other comparison algorithms around 5% less matching error on average.

• Korean Journal of Remote Sensing
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• v.26 no.1
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• pp.39-45
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• 2010

This study used the keypoint observed simultaneously on two images and on twodimensional intensity image data, which was obtained along with the two point clouds data that were approached for automatic focus among points on terrestrial LiDAR data, and selected matching point through SIFT algorithm. Also, for matching error diploid, RANSAC algorithm was applied to improve the accuracy of focus. As calculating the degree of three-dimensional rotating transformation, which is the transformation-type parameters between two points, and also the moving amounts of vertical/horizontal, the result was compared with the existing result by hand. As testing the building of College of Science at Konkuk University, the difference of the transformation parameters between the one through automatic matching and the one by hand showed 0.011m, 0.008m, and 0.052m in X, Y, Z directions, which concluded to be used as the data for automatic focus.

• Korean Journal of Remote Sensing
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• v.37 no.3
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• pp.567-575
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• 2021

In order to correct the provided RPC and DEM generated from the high-resolution satellite images, the acquisition of the ground control point (GCP) must be preceded. This task is a very complicate that requires field surveys, GPS surveying, and image coordinate reading corresponding to GCPs. In addition, since it is difficult to set up and measure a GCP in areas where access is difficult or impossible (tidal flats, polar regions, volcanic regions, etc.), an alternative method is needed. In this paper, we propose a 3D surface matching technique using only the established ground coordinate package, avoiding the ground-image-location survey of the GCP to correct the DEM produced from WorldView-2 satellite images and the provided RPCs. The location data of the public control points were obtained from the National Geographic Information Institute website, and the DEM was corrected by performing 3D surface matching with this package. The accuracy of 3-axis translation and rotation obtained by the matching was evaluated using pre-measured GPS checkpoints. As a result, it was possible to obtain results within 2 m in the plane location and 1 m in height.

• The Journal of the Acoustical Society of Korea
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• v.26 no.8
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• pp.415-425
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• 2007

This paper proposes a method of underwater source localization using the wideband interference patterns matching. By matching two interference patterns in the spectrogram, it is estimated a ratio of the range from source to sensor5, and then this ratio is applied to the Apollonius circle. The Apollonius circle is defined as the locus of all points whose distances from two fixed points are in a constant value so that it is possible to represent the locus of potential source location. The Apollonius circle alone, however still keeps the ambiguity against the correct source location. Therefore another equation is necessary to estimate the unique locus of the source location. By estimating time differences of signal arrivals between source and sensors, the hyperbola equation is used to get the cross point of the two equations, where the point being assumed to be the source position. Simulations are performed to get performances of the proposed algorithm. Also, comparisons with real sea experiment data are made to prove applicability of the algorithm in real environment. The results show that the proposed algorithm successfully estimates the source position within an error bound of 10%.