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

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2007.06a
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• pp.399-400
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• 2007

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1315-1318
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• 2004

Based on fuzzy 2-mean classification and template matching method, we propose a new algorithm to detect the edges of an image. In the algorithm, fuzzy 2-mean classification can classify all pixels in the mask into two clusters whatever the mask in the dark or light region; and template matching not only determines the edge's direction, but also thins the detected edge by a set of inference rules and, by the way, reduces the impulse noises.

• Korean Journal of Remote Sensing
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• v.23 no.4
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• pp.273-285
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• 2007

Most stereo matching methods use intensity values in small image patches to measure the correspondence between two points. If the noisy pixels are used in computing the corresponding point, the matching performance becomes low. For this reason, the noise plays a critical role in determining the matching performance. In this paper, we propose a method for combining intensity and edge filters robust to the noise in order to improve the performance of stereo matching using high resolution satellite imagery. We used intensity filters such as Mean, Median, Midpoint and Gaussian filter and edge filters such as Gradient, Roberts, Prewitt, Sobel and Laplacian filter. To evaluate the performance of intensity and edge filters, experiments were carried out on both synthetic images and satellite images with uniform or gaussian noise. Then each filter was ranked based on its performance. Among the intensity and edge filters, Median and Sobel filter showed best performance while Midpoint and Laplacian filter showed worst result. We used Ikonos satellite stereo imagery in the experiments and the matching method using Median and Sobel filter showed better matching results than other filter combinations.

• 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 the Korean Institute of Intelligent Systems
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• v.17 no.1
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• pp.94-99
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• 2007

In this paper, a 2-dimensional edge-based matching algorithm is proposed that combines the generalized Hough transform (GHT) and the Chamfer matching to complement weakness of either method. First, the GHT is used to find approximate object positions and orientations, and then these positions and orientations are used as starling parameter values to find more accurate position and orientation using the Chamfer matching. Finally, matching accuracy is further refined by using a subpixel algorithm. The algorithm was implemented and successfully tested on a number of images containing various electronic components.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10a
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• pp.859-863
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• 1993

There are two methods to get 3-dimensional information by matching image pair feature-based matching and area-based matching. One of the problems in the area-based matching is how the optimal search region which gives accurate correlation between given point and its neighbors can be selected. In this paper, we proposed a new area-based matching algorithm which uses edge-features used in the conventional feature-based matching. It first selects matching candidates by feature-based and matches image pair with area-based method by taking these candidates as guidance to decision of search area. The results show that running time is reduced by optimizing search area(considering edge points and continuity of disparity), keeping on the precision as the conventional area-based matching method.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.3D
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• pp.519-525
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• 2006

The traditional area-based matching or efficient matching methods using epipolar geometry and height restriction of stereo images, which have a confined search space for image matching, have still some disadvantages such as mismatching and timeconsuming, especially in the dense metropolitan city that very high and similar buildings exist. To solve these problems, a new image matching method through building recognition has been presented. This paper described building recognition in color stereo images using edge and color information as a elementary study of new matching scheme. We introduce the modified Hausdorff distance for using edge information, and the modified color indexing with 3-D RGB histogram for using color information. Color information or edge information alone is not enough to find conjugate building pairs. For edge information only, building recognition rate shows 46.5%, for color information only, 7.1%. However, building recognition rate distinctly increase 78.5% when both information are combined.

• Journal of information and communication convergence engineering
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• v.8 no.3
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• pp.339-342
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• 2010

An iris image pattern positioning with preserved edge detector, ring zone and clock zone, frequency distribution and overlay matching is presented in this paper. Edge detector is required to be powerful and detail. That is proposed by overlaying Canny with LOG (CLOG). The two reference patterns are made from allocating each gray level on the clock zone and ring zone respectively. The normalized target image is overlaid with the clock zone reference pattern and the ring zone pattern to extract overlapped number, and make a matched frequency distribution to look through a symptom and position of human organ and tissue. The iterating experiments result in the ring and clock zone positioning evaluation.

• Journal of the Institute of Convergence Signal Processing
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• v.7 no.1
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• pp.11-16
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• 2006

To manipulate large video databases, effective video indexing and retrieval are required. A large number of video indexing and retrieval algorithms have been presented for frame-w]so user query or video content query whereas a relatively few video sequence matching algorithms have been proposed for video sequence query. In this paper, we propose an efficient algorithm to extract key frames using color histograms and to match the video sequences using edge features. To effectively match video sequences with low computational load, we make use of the key frames extracted by the cumulative measure and the distance between key frames, and compare two sets of key frames using the modified Hausdorff distance. Experimental results with several real sequences show that the proposed video retrieval algorithm using color and edge features yields the higher accuracy and performance than conventional methods such as histogram difference, Euclidean metric, Battachaya distance, and directed divergence methods.