• Title/Summary/Keyword: mathematical image

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Ω-BIFUZZY SUBSEMIGROUPS IN SEMIGROUPS

  • HUR, KUL;JUN, YOUNG BAE;KANG, HEE WON
    • Honam Mathematical Journal
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    • v.27 no.1
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    • pp.31-41
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    • 2005
  • Given a set ${\Omega}$, the notion of an ${\Omega}$-bifuzzy subsemigroup in semigroups is given, and some properties are investigated. Homomorphic image and inverse image of an ${\Omega}$-bifuzzy subsemigroup are considered.

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An Effective Framework for Contented-Based Image Retrieval with Multi-Instance Learning Techniques

  • Peng, Yu;Wei, Kun-Juan;Zhang, Da-Li
    • Journal of Ubiquitous Convergence Technology
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    • v.1 no.1
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    • pp.18-22
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    • 2007
  • Multi-Instance Learning(MIL) performs well to deal with inherently ambiguity of images in multimedia retrieval. In this paper, an effective framework for Contented-Based Image Retrieval(CBIR) with MIL techniques is proposed, the effective mechanism is based on the image segmentation employing improved Mean Shift algorithm, and processes the segmentation results utilizing mathematical morphology, where the goal is to detect the semantic concepts contained in the query. Every sub-image detected is represented as a multiple features vector which is regarded as an instance. Each image is produced to a bag comprised of a flexible number of instances. And we apply a few number of MIL algorithms in this framework to perform the retrieval. Extensive experimental results illustrate the excellent performance in comparison with the existing methods of CBIR with MIL.

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Vehicle Detection in Tunnel using Gaussian Mixture Model and Mathematical Morphological Processing (가우시안 혼합모델과 수학적 형태학 처리를 이용한 터널 내에서의 차량 검출)

  • Kim, Hyun-Tae;Lee, Geun-Hoo;Park, Jang-Sik;Yu, Yun-Sik
    • The Journal of the Korea institute of electronic communication sciences
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    • v.7 no.5
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    • pp.967-974
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    • 2012
  • In this paper, a vehicle detection algorithm with HD CCTV camera images using GMM(Gaussian Mixture Model) algorithm and mathematical morphological processing is proposed. At the first stage, background could be estimated using GMM from CCTV input image signal and then object could be separated from difference image of the input image and background image. At the second stage, candidated object were reformed by using mathematical morphological processing. Finally, vehicle object could be detected using vehicle size informations depend on distance and vehicle type in tunnel. Through real experiments in tunnel, it is shown that the proposed system works well.

MULTI-APERTURE IMAGE PROCESSING USING DEEP LEARNING

  • GEONHO HWANG;CHANG HOON SONG;TAE KYUNG LEE;HOJUN NA;MYUNGJOO KANG
    • Journal of the Korean Society for Industrial and Applied Mathematics
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    • v.27 no.1
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    • pp.56-74
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    • 2023
  • In order to obtain practical and high-quality satellite images containing high-frequency components, a large aperture optical system is required, which has a limitation in that it greatly increases the payload weight. As an attempt to overcome the problem, many multi-aperture optical systems have been proposed, but in many cases, these optical systems do not include high-frequency components in all directions, and making such an high-quality image is an ill-posed problem. In this paper, we use deep learning to overcome the limitation. A deep learning model receives low-quality images as input, estimates the Point Spread Function, PSF, and combines them to output a single high-quality image. We model images obtained from three rectangular apertures arranged in a regular polygon shape. We also propose the Modulation Transfer Function Loss, MTF Loss, which can capture the high-frequency components of the images. We present qualitative and quantitative results obtained through experiments.

The Image of Derivations on Banach Algebras of Differential Functions

  • Park, Dal-Won
    • Journal of the Chungcheong Mathematical Society
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    • v.2 no.1
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    • pp.81-90
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    • 1989
  • Let $D:C^n(I){\longrightarrow}M$ be a derivation from the Banach algebra of n times continuously differentiable functions on an interval I into a Banach $C^n(I)$-module M. If D is continuous and D(z) is contained in the k-differential subspace, the image of D is contained in the k-differential subspace. The question of when the image of a derivation is contained in the k-differential subspace is discussed.

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Image Segmentation Improvement by Selective Application Structuring Element of Mathematical Morphology (수리 형태학의 선택적 구조요소 적용에 의한 영상 분할의 성능 개선)

  • 오재현;김성곤;김종협;신홍규;김환용
    • Proceedings of the IEEK Conference
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    • 2003.07e
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    • pp.1972-1975
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    • 2003
  • Video segmentation is an essential part in region-based video coding and any other fields of the video processing. Among lots of methods proposed so far, the watershed method in which the region growing is performed for the gradient image can produce well-partitioned regions globally without any influence on local noise and extracts accurate boundaries. But, it generates a great number of small regions, which we call over segmentation problem. Therefore we proposes image segmentation improvement by selective application structuring element of mathematical morphology.

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MAPPINGS OF CUBIC SETS

  • Kang, Jeong Gi;Kim, Chang Su
    • Communications of the Korean Mathematical Society
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    • v.31 no.3
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    • pp.423-431
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    • 2016
  • Images and inverse images of (almost) stable cubic sets are discussed. We show that the image and inverse image of stable cubic sets are also stable. Conditions for the image of almost cubic sets to be an almost cubic set are provided. The complement, the P-union and the P-intersection of (inverse) images of (almost) stable cubic sets are considered.

GLOBAL GENERALIZED CROSS VALIDATION IN THE PRECONDITIONED GL-LSQR

  • Chung, Seiyoung;Oh, SeYoung;Kwon, SunJoo
    • Journal of the Chungcheong Mathematical Society
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    • v.32 no.1
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    • pp.149-156
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    • 2019
  • This paper present the global generalized cross validation as the appropriate choice of the regularization parameter in the preconditioned Gl-LSQR method in solving image deblurring problems. The regularization parameter, chosen from the global generalized cross validation, with preconditioned Gl-LSQR method can give better reconstructions of the true image than other parameters considered in this study.

Control of an Omni-directional Mobile Robot Based on Camera Image (카메라 영상기반 전방향 이동 로봇의 제어)

  • Kim, Bong Kyu;Ryoo, Jung Rae
    • Journal of the Korean Institute of Intelligent Systems
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    • v.24 no.1
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    • pp.84-89
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    • 2014
  • In this paper, an image-based visual servo control strategy for tracking a target object is applied to a camera-mounted omni-directional mobile robot. In order to get target angular velocity of each wheel from image coordinates of the target object, in general, a mathematical image Jacobian matrix is built using a camera model and a mobile robot kinematics. Unlike to the well-known mathematical image Jacobian, a simple rule-based control strategy is proposed to generate target angular velocities of the wheels in conjunction with size of the target object captured in a camera image. A camera image is divided into several regions, and a pre-defined rule corresponding to the target-located image region is applied to generate target angular velocities of wheels. The proposed algorithm is easily implementable in that no mathematical description for image Jacobian is required and a small number of rules are sufficient for target tracking. Experimental results are presented with descriptions about the overall experimental system.