• Title/Summary/Keyword: Robust Search Algorithm

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Shrink-Wrapped Boundary Face Algorithm for Surface Reconstruction from Unorganized 3D Points (비정렬 3차원 측정점으로부터의 표면 재구성을 위한 경계면 축소포장 알고리즘)

  • 최영규;구본기;진성일
    • Journal of KIISE:Computer Systems and Theory
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    • v.31 no.10
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    • pp.593-602
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    • 2004
  • A new surface reconstruction scheme for approximating the surface from a set of unorganized 3D points is proposed. Our method, called shrink-wrapped boundary face (SWBF) algorithm, produces the final surface by iteratively shrinking the initial mesh generated from the definition of the boundary faces. Proposed method surmounts the genus-0 spherical topology restriction of previous shrink-wrapping based mesh generation technique, and can be applicable to any kind of surface topology. Furthermore, SWBF is much faster than the previous one since it requires only local nearest-point-search in the shrinking process. According to experiments, it is proved to be very robust and efficient for mesh generation from unorganized points cloud.

A Study on Design of Optimal Satellite-Tracking Antenna $H{\infty}$ Control System (최적 위성추적 안테나 $H{\infty}$ 제어 시스템의 설계에 관한 연구)

  • Kim, Dong-Wan;Jeong, Ho-Seong;Hwang, Hyun-Joon
    • Journal of IKEEE
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    • v.1 no.1 s.1
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    • pp.19-30
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    • 1997
  • In this paper we design the optimal satellite-tracking antenna $H{\infty}$ control system using genetic algorithms. To do this, we give gain and dynamics parameters to the weighting functions and apply genetic algorithms with reference model to the optimal determination of weighting functions and design parameter ${\gamma}$ that are given by Glover-Doyle algorithm which can design $H{\infty}$ controller in the state space. These weighting functions and design parameter ${\gamma}$ are optimized simultaneously in the search domain guaranteeing the robust stability of closed-loop system. The effectiveness of this satellite-tracking antenna $H{\infty}$ control system is verified by computer simulation.

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Naive Bayes Learner for Propositionalized Attribute Taxonomy (명제화된 어트리뷰트 택소노미를 이용하는 나이브 베이스 학습 알고리즘)

  • Kang, Dae-Ki
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2008.10a
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    • pp.406-409
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    • 2008
  • We consider the problem of exploiting a taxonomy of propositionalized attributes in order to learn compact and robust classifiers. We introduce Propositionalized Attribute Taxonomy guided Naive Bayes Learner (PAT-NBL), an inductive learning algorithm that exploits a taxonomy of propositionalized attributes as prior knowledge to generate compact and accurate classifiers. PAT-NBL uses top-down and bottom-up search to find a locally optimal cut that corresponds to the instance space from propositionalized attribute taxonomy and data. Our experimental results on University of California-Irvine (UCI) repository data sets show that the proposed algorithm can generate a classifier that is sometimes comparably compact and accurate to those produced by standard Naive Bayes learners.

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Robust Object Tracking based on Weight Control in Particle Swarm Optimization (파티클 스웜 최적화에서의 가중치 조절에 기반한 강인한 객체 추적 알고리즘)

  • Kang, Kyuchang;Bae, Changseok;Chung, Yuk Ying
    • The Journal of Korean Institute of Next Generation Computing
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    • v.14 no.6
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    • pp.15-29
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    • 2018
  • This paper proposes an enhanced object tracking algorithm to compensate the lack of temporal information in existing particle swarm optimization based object trackers using the trajectory of the target object. The proposed scheme also enables the tracking and documentation of the location of an online updated set of distractions. Based on the trajectories information and the distraction set, a rule based approach with adaptive parameters is utilized for occlusion detection and determination of the target position. Compare to existing algorithms, the proposed approach provides more comprehensive use of available information and does not require manual adjustment of threshold values. Moreover, an effective weight adjustment function is proposed to alleviate the diversity loss and pre-mature convergence problem in particle swarm optimization. The proposed weight function ensures particles to search thoroughly in the frame before convergence to an optimum solution. In the existence of multiple objects with similar feature composition, this algorithm is tested to significantly reduce convergence to nearby distractions compared to the other existing swarm intelligence based object trackers.

Line Drawings from 2D Images (이차원 영상의 라인 드로잉)

  • Son, Min-Jung;Lee, Seung-Yong
    • Journal of KIISE:Computer Systems and Theory
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    • v.34 no.12
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    • pp.665-682
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    • 2007
  • Line drawing is a widely used style in non-photorealistic rendering because it generates expressive descriptions of object shapes with a set of strokes. Although various techniques for line drawing of 3D objects have been developed, line drawing of 2D images has attracted little attention despite interesting applications, such as image stylization. This paper presents a robust and effective technique for generating line drawings from 2D images. The algorithm consists of three parts; filtering, linking, and stylization. In the filtering process, it constructs a likelihood function that estimates possible positions of lines in an image. In the linking process, line strokes are extracted from the likelihood function using clustering and graph search algorithms. In the stylization process, it generates various kinds of line drawings by applying curve fitting and texture mapping to the extracted line strokes. Experimental results demonstrate that the proposed technique can be applied to the various kinds of line drawings from 2D images with detail control.

Multispectral Mural Underdrawing Mosaic Technique (다중스펙트럼 기반 벽화 밑그림 영상 모자익 기법)

  • 이태성;권용무;고한석
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.41 no.5
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    • pp.175-183
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    • 2004
  • In this paper, we propose a new accurate and robust image mosaic technique of the mural underdrawing taken from the infra-red camera, which is based on multiple image registration and adaptive blending technique. The image mosaicing methods which have been developed so far have the following deficits. It is hard to generate a high resolution image when there are regions that do not have features or intensity gradients, and there is a trade-off in overlapping region size in view of registration and blending. We consider these issues as follows. First, in order to mosaic images with neither noticeable features nor intensity gradients, we use a projected supplementary pattern and pseudo color image for features in the image pieces which are registered. Second, we search the overlapping region size with minimum blending error between two adjacent images and then apply blending technique to minimum error overlapping region. Finally, we could find our proposed method is more effective and efficient for image mosaicing than conventional mosaic techniques and also is more adequate for the application of infra-red mural underdrawing mosaicing. Experimental results show the accuracy and robustness of the algorithm

Digital Image Watermarking using Subband Correlation Wavelet Domain (웨이블릿 영역의 부대역 상관도를 이용한 디지털 영상 워터마킹)

  • 서영호;박진영;김동욱
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.40 no.6
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    • pp.51-60
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    • 2003
  • The watermarking is the technique that embeds or extracts the certain data without the change of the original data for the copyright protection of the multimedia contents. Watermark-embedded contents must not be distinguished by human's eye and must be robust to the various image processing and the intentional distortions. In this paper, we propose a new watermarking technique applied in the wavelet domain which has both the spatial and frequency information of a image. For both the robustness and the invisibility, the positions for embedding the watermark is selected with the multi-threshold. We search the similarity between highly correlated coefficients in the each subband and decide the mark space after verifying the significance in the specified subband. The similarity is represented by the coefficient difference between the subbands and its distribution is used in the watermark embedding and extracting. The embedded watermark can be extracted without the original image using the relationship of the subbands. By these properties the proposed watermarking algorithm has the invisibility and the robustness to the attacks such as JPEG compression and the general image processing.

Part-based Hand Detection Using HOG (HOG를 이용한 파트 기반 손 검출 알고리즘)

  • Baek, Jeonghyun;Kim, Jisu;Yoon, Changyong;Kim, Dong-Yeon;Kim, Euntai
    • Journal of the Korean Institute of Intelligent Systems
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    • v.23 no.6
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    • pp.551-557
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    • 2013
  • In intelligent robot research, hand gesture recognition has been an important issue. And techniques that recognize simple gestures are commercialized in smart phone, smart TV for swiping screen or volume control. For gesture recognition, robust hand detection is important and necessary but it is challenging because hand shape is complex and hard to be detected in cluttered background, variant illumination. In this paper, we propose efficient hand detection algorithm for detecting pointing hand for recognition of place where user pointed. To minimize false detections, ROIs are generated within the compact search region using skin color detection result. The ROIs are verified by HOG-SVM and pointing direction is computed by both detection results of head-shoulder and hand. In experiment, it is shown that proposed method shows good performance for hand detection.

RCGA-Based States Observer Design of Container Crane concerned with Design Specification (설계사양을 고려한 컨테이너 크레인의 RCGA기반 상태 관측기 설계)

  • Lee, Soo-Lyong;Ahn, Jong-Kap;Lee, Yun-Hyung;Son, Jeong-Ki;So, Myung-Ok
    • Journal of Navigation and Port Research
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    • v.32 no.10
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    • pp.851-856
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    • 2008
  • Construction of large-scale container ports with the productivity improvements in container cranes shortened time of staying port to increase the level of service it harbors efforts accelerated. About container crane system exerted on the input, which is designed to look good performance considering the states feedback control system. The states observer designed of container cranes state variables that are expected to measurement noise or particular measurement signal. In the status of existing research, the feedback gain matrix and the state observer gain matrix are searched by being separated solving. But the feedback gain matrix and the state observer gain matrix are searched by RCGAs at once that be used robust search method in this paper.

Audio Fingerprint Extraction Method Using Multi-Level Quantization Scheme (다중 레벨 양자화 기법을 적용한 오디오 핑거프린트 추출 방법)

  • Song Won-Sik;Park Man-Soo;Kim Hoi-Rin
    • The Journal of the Acoustical Society of Korea
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    • v.25 no.4
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    • pp.151-158
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    • 2006
  • In this paper, we proposed a new audio fingerprint extraction method, based on Philips' music retrieval algorithm, which uses the energy difference of neighboring filter-bank and probabilistic characteristics of music. Since Philips method uses too many filter-banks in limited frequency band, it may cause audio fingerprints to be highly sensitive to additive noises and to have too high correlation between neighboring bands. The proposed method improves robustness to noises by reducing the number of filter-banks while it maintains the discriminative power by representing the energy difference of bands with 2 bits where the quantization levels are determined by probabilistic characteristics. The correlation which exists among 4 different levels in 2 bits is not only utilized in similarity measurement. but also in efficient reduction of searching area. Experiments show that the proposed method is not only more robust to various environmental noises (street, department, car, office, and restaurant), but also takes less time for database search than Philips in the case where music is highly degraded.