• The KIPS Transactions:PartB
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• v.9B no.5
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• pp.579-586
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• 2002

The edge descriptor proposed by MPEG-7 standard is a representative approach for the contents-based image retrieval using the edge information. In the edge descriptor, the edge information is the edge histogram derived from a gray-level value image. This paper proposes a new method which extracts color edge information from color images and a new approach for the contents-based image retrieval based on the color edge histogram. The poposed method and technique are applied to image retrieval of the e-catalogue. For the evaluation, the results of image retrieval using the proposed approach are compared with those of image retrieval using the edge descriptor by MPEG-7 and the statistics shows the efficiency of the proposed method. The proposed color edge model is made by combining the R,G,B channel components vectorially and by characterizing the vector norm of the edge map. The color edge histogram using the direction of the color edge model is subsequently used for the contents-based image retrieval.

• Journal of Broadcast Engineering
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• v.3 no.2
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• pp.127-137
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• 1998

In this paper, we propose the method of extracting edge information from MPEG video sequences for the detection of scene changes. In a the proposed method, five significant AC coefficients of each MPEG block are utilized to obtain edge images from the MPEG video. AC edge images obtained by the proposed scheme not only produce better object boundary information than conventional methods using only DC coefficients, but also can reduce the boundary effects produced by DC-based. Since the AC edge image contains the content information of each frame, it can be effectively utilized for the detection of scene change as well as the content-based video query. Experimental results show that the proposed method can be effectively utilized for the detection of scene changes.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.14 no.3
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• pp.249-262
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• 1989

We present a method of boundary extraction of moving objects. We propose four methods for detecting moving edge pixels which can be located on the boundaries of moving objects. We select the best one after we test the above four methods to real image sequences. The portion of the boundaries of moving objects which is marked as moving edge pixels is searched along the moving edge pixels with simple heuristics. And the end points of the resultant line segments are utilized as the start points of the secon stage heuristic search. This second stage search is performed for the boundaries of moving objects which is not marked as moving edge pixels due to various reasons. We test our algorithm for two real sequences and we find that this simple algorithm has good performance.

• Journal of the Korean Society for Precision Engineering
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• v.10 no.4
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• pp.170-179
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• 1993

In this study, self-organized neural network is used to solve the vorrespondence problem of the axial stereo image. Edge points are extracted from a pair of stereo images and then the edge points of rear image are assined to the output nodes of neural network. In the matching process, the two input nodes of neural networks are supplied with the coordi- nates of the edge point selected randomly from the front image. This input data activate optimal output node and its neighbor nodes whose coordinates are thought to be correspondence point for the present input data, and then their weights are allowed to updated. After several iterations of updating, the weights whose coordinates represent rear edge point are converged to the coordinates of the correspondence points in the front image. Because of the feature map properties of self-organized neural network, noise-free and smoothed depth data can be achieved.

• Journal of Digital Policy
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• v.1 no.2
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• pp.53-59
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• 2022

In this paper, we proposed a method using sub-edge information extracted through a hierarchical structure in the process of generating super resolution based on a single image. In order to improve the quality of super resolution, it is necessary to clearly distinguish the shape of each area while clearly expressing the boundary area in the image. The proposed method assists edge information of the image in deep learning based super resolution method to create an improved super resolution result while maintaining the structural shape of the boundary region, which is an important factor determining the quality in the super resolution process. In addition to the group convolution structure for performing deep learning based super resolution, a separate hierarchical edge accumulation extraction process based on high-frequency band information for sub-edge extraction is proposed, and a method of using it as an auxiliary feature is proposed. Experimental results showed about 1% performance improvement in PSNR and SSIM compared to the existing super resolution.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.42 no.3 s.303
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• pp.91-98
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• 2005

In this paper, we propose a temporal error concealment method based on the edge adaptive masking. In the method, four regions around the corrupted block - top, bottom, left, and right - are defined and the edge features of the regions are extracted by applying an edge operator for each direction. The size of a mask for the boundary matching is determined by the edge information, which can be considered as a criterion to measure the activity of the boundary region. In other words, it is determined such that the size of the mask is proportional to the amount of edge-component extracted from each region in order to yield the higher reliability on boundary matching. This process is equivalent to applying weights depending on the edge features, which leads the improved motion vector. In experiments, it is verified that the proposed method outperforms the conventional methods in terms of image quality, and then its merits and demerits are discussed.

• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.6
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• pp.709-713
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• 2005

A new algorithm is proposed for the extraction of line segments to construct 3D wire-frame models of building from the high-resolution aerial images. The purpose of this study Is the accurate and effective extraction of line segments, considering the problems such as discordance of lines and blurred edges existing in the conventional methods. Using the edge map extracted from aerial images, chain code tracking of edges was performed. Then, we extract the line segments considering the strength of edges and the direction of them. SUSAN (Smallest Uni-value Segment Assimilating Nucleus) algorithm proposed by Smith was used to extract an edge map. The proposed algorithm consists of 4 steps: removal of the horizontal, vertical and diagonal components of edges to reduce non-candidate point of line segments based on the chain code tracking of the edge map, removal of contiguous points, removal of the same angle points, and the extraction of the start and end points to be line segments. By comparing the proposed algorithm with Boldt algorithm, better results were obtained regarding the extraction of the representative line segments of buildings, having relatively less extraction of unnecessary line segments.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.30 no.2
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• pp.163-171
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• 2012

High resolution satellite images have been used for building and road system analysis, landscape analysis, and ecological assessment for several years. However, in high resolution satellite images, shadows are necessarily cast by manmade objects such as buildings and over-pass bridges. This paper develops the shadow extraction procedures in urban area including various land-use classes, and the extracted shadow areas are evaluated by a manually digitized shadow map. For the shadow extraction, the Canny edge operator and the dilation filter are applied to make building edge buffer area. Also, the object-based segmentation was performed using Gram-Schmitt fusion image, and spectral and spatial parameters are calculated from the segmentation results. Finally, we proposed appropriate parameters and extraction rules for the shadow extraction. The accuracy of the shadow extraction results from the various assessment indices is 80% to 90%.

• Journal of the Korea Society of Computer and Information
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• v.15 no.11
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• pp.75-82
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• 2010

The paper proposed CBIRS/EFI with contents based search technique using edge feature information of the object from image information of the object which is uncertain. In order to search specially efficiently case of partial image information of the object, we used the search technique which extracts outline information and color information in feature information of object. In order to experiment this, we extracted side edge feature information of the vehicle for feature information of the object after capture the car image of the underground garage. This is the system which applies a contents base search by the result which analyzes the image which extracts a feature, an original image to search and a last similar measurement result. This system compared in FE-CBIRS systems which are an existing feature extraction contents base image retrieval system and the function which improves the accuracy and an effectiveness of search rate was complemented. The performance appraisal of CBIRS/EFI systems applied edge extraction feature information and color information of the cars. And we compared a color feature search time, a shape characteristic search time and a search rate from the process which searches area feature information. We extracted the case 91.84% of car edge feature extraction rate. And a average search time of CBIRS/EFI is showing a difference of average 0.4-0.9 seconds than FE-CBIRS from vehicle. color search time, shape characteristic search time and similar search time. So, it was proven with the fact that is excellent.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.7 no.5
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• pp.993-1001
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• 2003

A RDB Storage Model based on the Edge-Labeled Graph is suggested for store the XML instance in Relational Databases(RDB). The XML instance being stored is represented by Data Graph based on the Edge-Labeled Graph. Data Path Table, Element, Attribute, and Table Index Table values are extracted. Then Database Schema is defined, and the extracted values are stored using the Mapper. In order to support querry, Repository Model offers the translator translating XQL which is used as query language under XPATH, into SQL. In addition, it creates DBtoXML generator restoring the stored XML instance. As a result, storage relationship between the XML instance and proposed model structure can be expressed in terms of Graph-based Path, and it shows the possibility of easy search of random Element and Attribute information.