• Title/Summary/Keyword: 에지정의

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Image segmentation using fuzzy worm searching and adaptive MIN-MAX clustering based on genetic algorithm (유전 알고리즘에 기반한 퍼지 벌레 검색과 자율 적응 최소-최대 군집화를 이용한 영상 영역화)

  • Ha, Seong-Wook;Kang, Dae-Seong;Kim, Dai-Jin
    • Journal of the Korean Institute of Telematics and Electronics S
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    • v.35S no.12
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    • pp.109-120
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    • 1998
  • An image segmentation approach based on the fuzzy worm searching and MIN-MAX clustering algorithm is proposed in this paper. This algorithm deals with fuzzy worm value and min-max node at a gross scene level, which investigates the edge information including fuzzy worm action and spatial relationship of the pixels as the parameters of its objective function. But the conventional segmentation methods for edge extraction generally need the mask information for the algebraic model, and take long run times at mask operation, whereas the proposed algorithm has single operation according to active searching of fuzzy worms. In addition, we also propose both genetic fuzzy worm searching and genetic min-max clustering using genetic algorithm to complete clustering and fuzzy searching on grey-histogram of image for the optimum solution, which can automatically determine the size of ranges and has both strong robust and speedy calculation. The simulation results showed that the proposed algorithm adaptively divided the quantized images in histogram region and performed single searching methods, significantly alleviating the increase of the computational load and the memory requirements.

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Mesh Simplification for Preservation of Characteristic Features using Surface Orientation (표면의 방향정보를 고려한 메쉬의 특성정보의 보존)

  • 고명철;최윤철
    • Journal of Korea Multimedia Society
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    • v.5 no.4
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    • pp.458-467
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    • 2002
  • There has been proposed many simplification algorithms for effectively decreasing large-volumed polygonal surface data. These algorithms apply their own cost function for collapse to one of fundamental simplification unit, such as vertex, edge and triangle, and minimize the simplification error occurred in each simplification steps. Most of cost functions adopted in existing works use the error estimation method based on distance optimization. Unfortunately, it is hard to define the local characteristics of surface data using distance factor alone, which is basically scalar component. Therefore, the algorithms cannot preserve the characteristic features in surface areas with high curvature and, consequently, loss the detailed shape of original mesh in high simplification ratio. In this paper, we consider the vector component, such as surface orientation, as one of factors for cost function. The surface orientation is independent upon scalar component, distance value. This means that we can reconsider whether or not to preserve them as the amount of vector component, although they are elements with low scalar values. In addition, we develop a simplification algorithm based on half-edge collapse manner, which use the proposed cost function as the criterion for removing elements. In half-edge collapse, using one of endpoints in the edge represents a new vertex after collapse operation. The approach is memory efficient and effectively applicable to the rendering system requiring real-time transmission of large-volumed surface data.

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Extraction of UAV Image Sharpness Index Using Edge Target Analysis (에지 타겟 분석을 통한 무인기 영상의 선명도 지표 추출)

  • Lim, Pyung-Chae;Seo, Junghoon;Kim, Taejung
    • Korean Journal of Remote Sensing
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    • v.34 no.6_1
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    • pp.905-923
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    • 2018
  • In order to generate high-resolution products using UAV images, it is necessary to analyze the sharpness of the themselves measured through image analysis. When images that have unclear sharpness of UAV are used in the production, they can have a great influence on operations such as acquisition and mapping of accurate three-dimensional information using UAV. GRD (Ground Resolved Distance) has been used as an indicator of image clarity. GRD is defined as the minimum distance between two identifiable objects in an image and is used as a concept against the GSD (Ground Sampling Distance), which is a spatial sample interval. In this study, GRD is extracted by analyzing the edge target without visual analysis. In particular, GRD to GSD ratio (GRD/GSD), or GRD expressed in pixels, is used as an index for evaluation the relative image sharpness. In this paper, GRD is calculated by analyzing edge targets at various altitudes in various shooting environments using a rotary wing. Using GRD/GSD, it was possible to identify images whose sharpness was significantly lowered, and the appropriateness of the image as an image clarity index was confirmed.

A Study for Depth-map Generation using Vanishing Point (소실점을 이용한 Depth-map 생성에 관한 연구)

  • Kim, Jong-Chan;Ban, Kyeong-Jin;Kim, Chee-Yong
    • Journal of Korea Multimedia Society
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    • v.14 no.2
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    • pp.329-338
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    • 2011
  • Recent augmentation reality demands more realistic multimedia data with the mixture of various media. High-technology for multimedia data which combines existing media data with various media such as audio and video dominates entire media industries. In particular, there is a growing need to serve augmentation reality, 3-dimensional contents and realtime interaction system development which are communication method and visualization tool in Internet. The existing services do not correspond to generate depth value for 3-dimensional space structure recovery which is to form solidity in existing contents. Therefore, it requires research for effective depth-map generation using 2-dimensional video. Complementing shortcomings of existing depth-map generation method using 2-dimensional video, this paper proposes an enhanced depth-map generation method that defines the depth direction in regard to loss location in a video in which none of existing algorithms has defined.

Semi-automatic 3D Building Reconstruction from Uncalibrated Images (비교정 영상에서의 반자동 3차원 건물 모델링)

  • Jang, Kyung-Ho;Jang, Jae-Seok;Lee, Seok-Jun;Jung, Soon-Ki
    • Journal of Korea Multimedia Society
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    • v.12 no.9
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    • pp.1217-1232
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    • 2009
  • In this paper, we propose a semi-automatic 3D building reconstruction method using uncalibrated images which includes the facade of target building. First, we extract feature points in all images and find corresponding points between each pair of images. Second, we extract lines on each image and estimate the vanishing points. Extracted lines are grouped with respect to their corresponding vanishing points. The adjacency graph is used to organize the image sequence based on the number of corresponding points between image pairs and camera calibration is performed. The initial solid model can be generated by some user interactions using grouped lines and camera pose information. From initial solid model, a detailed building model is reconstructed by a combination of predefined basic Euler operators on half-edge data structure. Automatically computed geometric information is visualized to help user's interaction during the detail modeling process. The proposed system allow the user to get a 3D building model with less user interaction by augmenting various automatically generated geometric information.

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Approximation Algorithms for a Minimum-Diameter Spanning Tree (최소 지름 신장 트리를 구하는 근사 알고리즘)

  • 신찬수;박상민
    • Journal of KIISE:Computer Systems and Theory
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    • v.30 no.5_6
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    • pp.319-323
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    • 2003
  • Let P be a set of n points in the plane. A minimum spanning tree(MST) is a spanning tree connecting n points of P such that the sum of lengths of edges of the tree is minimized. A diameter of a tree is the maximum length of paths connecting two points of a spanning tree of P. The problem considered in this paper is to compute the spanning tree whose diameter is minimized over all spanning trees of P. We call such tree a minimum-diameter spanning tree(MDST). The best known previous algorithm[3] finds MDST in $O(n^2)$ time. In this paper, we suggest an approximation algorithm to compute a spanning tree whose diameter is no more than 5/4 times that of MDST, running in O(n$^2$log$^2$n) time. This is the first approximation algorithm on the MDST problem.

A Fast Fractal Image Compression Using The Normalized Variance (정규화된 분산을 이용한 프랙탈 압축방법)

  • Kim, Jong-Koo;Hamn, Do-Yong;Wee, Young-Cheul;Kimn, Ha-Jine
    • The KIPS Transactions:PartA
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    • v.8A no.4
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    • pp.499-502
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    • 2001
  • Fractal image coding suffers from the long search time of domain pool although it provides many properties including the high compression ratio. We find that the normalized variance of a block is independent of contrast, brightness. Using this observation, we introduce a self similar block searching method employing the d-dimensional nearest neighbor searching. This method takes Ο(log/N) time for searching the self similar domain blocks for each range block where N is the number of domain blocks. PSNR (Peak Signal Noise Ratio) of this method is similar to that of the full search method that requires Ο(N) time for each range block. Moreover, the image quality of this method is independent of the number of edges in the image.

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Simplified Depth Modeling in HEVC-based 3D Video Coding (HEVC-기반 3차원 비디오 부호화에서 깊이 모델링 간소화 방법)

  • Song, Yunseok;Ho, Yo-Sung
    • Smart Media Journal
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    • v.2 no.2
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    • pp.28-32
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    • 2013
  • In this paper, we present a method to reduce complexity of depth modeling modes (DMM) that are used in the current 3D-HEVC standardization. DMM adds four modes to the existing HEVC intra prediction modes for accurate object edge representation in the depth map. Especially, Mode 3 requires distortion calculation of numerous pre-defined wedgelets, inducing high complexity. The proposed method employs absolute differences of neighboring pixels in the sides of the reference block to find high intensity changing positions. Based on such positions, the number of wedgelet candidates is reduced to six and distortion calculation is skipped for irrelevant wedgelets. Experimental results show complexity reduction by 3.1% on average, while maintaining similar coding performance.

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Recognition of Facial Expressions of Animation Characters Using Dominant Colors and Feature Points (주색상과 특징점을 이용한 애니메이션 캐릭터의 표정인식)

  • Jang, Seok-Woo;Kim, Gye-Young;Na, Hyun-Suk
    • The KIPS Transactions:PartB
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    • v.18B no.6
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    • pp.375-384
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    • 2011
  • This paper suggests a method to recognize facial expressions of animation characters by means of dominant colors and feature points. The proposed method defines a simplified mesh model adequate for the animation character and detects its face and facial components by using dominant colors. It also extracts edge-based feature points for each facial component. It then classifies the feature points into corresponding AUs(action units) through neural network, and finally recognizes character facial expressions with the suggested AU specification. Experimental results show that the suggested method can recognize facial expressions of animation characters reliably.

Locating Text in Web Images Using Image Based Approaches (웹 이미지로부터 이미지기반 문자추출)

  • Chin, Seongah;Choo, Moonwon
    • Journal of Intelligence and Information Systems
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    • v.8 no.1
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    • pp.27-39
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    • 2002
  • A locating text technique capable of locating and extracting text blocks in various Web images is presented here. Until now this area of work has been ignored by researchers even if this sort of text may be meaningful for internet users. The algorithms associated with the technique work without prior knowledge of the text orientation, size or font. In the work presented in this research, our text extraction algorithm utilizes useful edge detection followed by histogram analysis on the genuine characteristics of letters defined by text clustering region, to properly perform extraction of the text region that does not depend on font styles and sizes. By a number of experiments we have showed impressively acceptable results.

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