• Proceedings of the KIEE Conference
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• 2005.10b
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• pp.12-14
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• 2005

In this paper, we proposed an temporal error concealment (EC) using the proposed boundary matching method and the adaptive block matching method. The proposed boundary matching method improves the spatial correlation of the macroblocks (MBs) by reusing the pixels of the concealed MB to estimate a motion vector of a error MB. The adaptive block matching method inspects the horizontal edge and the vertical edge feature of a error MB surroundings, and it conceals the error MBs in reference to more stronger edge feature. This improves video quality by raising edge connection feature of the error MBs and the neighborhood MBs. In particular, we restore a lost MB as the unit of 8${\times}$16 block or 16${\times}$8 block by using edge feature from the surrounding macroblocks. Experimental results show that the proposed algorithm gives better results than the conventional algorithms from a subjective and an objective viewpoint.

• ETRI Journal
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• v.24 no.1
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• pp.23-30
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• 2002

MPEG-7 Visual Standard specifies a set of descriptors that can be used to measure similarity in images or video. Among them, the Edge Histogram Descriptor describes edge distribution with a histogram based on local edge distribution in an image. Since the Edge Histogram Descriptor recommended for the MPEG-7 standard represents only local edge distribution in the image, the matching performance for image retrieval may not be satisfactory. This paper proposes the use of global and semi-local edge histograms generated directly from the local histogram bins to increase the matching performance. Then, the global, semi-global, and local histograms of images are combined to measure the image similarity and are compared with the MPEG-7 descriptor of the local-only histogram. Since we exploit the absolute location of the edge in the image as well as its global composition, the proposed matching method can retrieve semantically similar images. Experiments on MPEG-7 test images show that the proposed method yields better retrieval performance by an amount of 0.04 in ANMRR, which shows a significant difference in visual inspection.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.3
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• pp.264-268
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• 2010

The purpose of this paper is to propose new techniques to match measured optical images by using the edge abstraction method and differentiation method based on image processing technology. To do this, we detect the matching template and non-matching template from each optical image. And then, we detect the edge parts of the overlaped image from comer edge abstraction method and remove noise image. At last, these data are related to applied first-order derivative operator. Finally, we show the effectiveness and feasibility of the proposed method through some experiments.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.32B no.12
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• pp.1591-1602
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• 1995

A hybrid approach which includes edge- and region-based methods is considered. The modified non-linear Laplacian(MNL) filter is used for feature extraction. The matching algorithm has three steps which are edge, signed region, and residual region matching. At first, the edge points are matched using the sign and direction of edges. Then, the disparity is propagated from edge to inside region. A variable window is used to consider the local method which give accurate matched points and area-based method which can obtain full-resolution disparity map. In addition, a new relaxation algorithm for considering matching possibility derived from normalized error and regional continuity constraint is proposed to reduce the mismatched points. By the result of simulation for various images, this algorithm is insensitive to noise and gives full- resolution disparity map.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.5
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• pp.493-498
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• 2007

In this paper, a 2-dimensional accurate edge-based matching algorithm using subpixel edges is proposed that combines the Generalized Hough Transform(GHT) and the Chamfer matching to complement the weakness of either method. First, the GHT is used to find the approximate object positions and orientations, and then these positions and orientations are used as starting parameter values to find more accurate position and orientation using the Chamfer matching with distance interpolation. Finally, matching accuracy is further refined by using a subpixel algorithm. Testing results demonstrate that greater matching accuracy is achieved using subpixel edges rather than edge pixels.

• Proceedings of the KIEE Conference
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• 1998.07g
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• pp.2225-2227
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• 1998

An efficient stereo matching method with variable matching weights is proposed. The edge segment-based stereo matching has been shown to be efficient method. The method includes 5 matching factor with different weights. The ordinary matching weights are not always adequate for every image. Employing different weight sets depending on the complexity shows better matching performance. In this paper, an evaluation criterion for complexity is suggested and the experimental results with the proposed method is shown.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.05a
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• pp.385-388
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• 2013

In this paper, we show the weakness of the image matching method by using MPEG-7 EHD(Edge Histogram Descriptor) and suggest how to improve this weakness by using image normalization. EHD algorithm is an image matching technique that collects edge's slope of distribution and same distribution. However, the EHD error rate is high because EHD is sensitive for changes of object distortion and rotation that will be matched. We improve matching performance by accurately extract edge information in image by using normalization. We compare and analyze the normalized EHD algorithm by using distortion and rotation and it shows robustness for changes of the size and rotation.

• 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.

• Journal of the Korea Society of Computer and Information
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• v.13 no.6
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• pp.1-12
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• 2008

This paper presents automatic moving object detection method using the rotating camera covering larger area with a single camera. The proposed method is based on the edge segment matching which robust to the dynamic environment with illumination change and background movement. The proposed algorithm presents an edge segment based background panorama image generation method minimizing the distortion due to image stitching, the background image generation method using Generalized Hough Transformation which can reliably register the current image to the panorama image overcoming the stitching distortions, the moving edge segment extraction method that overcome viewpoint difference and distortion. The experimental results show that the proposed method can detect correctly moving object under illumination change and camera vibration.

• 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.