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A geometric model for active contours in image processing

Authors:

Vicent Caselles,

Francine Catté,

Françoise DibosAuthors Info & Claims

Numerische Mathematik, Volume 66, Issue 1

Pages 1 - 31

https://doi.org/10.1007/BF01385685

Published: 01 December 1993 Publication History

Abstract

We propose a new model for active contours based on a geometric partial differential equation. Our model is intrinsec, stable (satisfies the maximum principle) and permits a rigorous mathematical analysis. It enables us to extract smooth shapes (we cannot retrieve angles) and it can be adapted to find several contours simultaneously. Moreover, as a consequence of the stability, we can design robust algorithms which can be engineed with no parameters in applications. Numerical experiments are presented.

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Cited By

Deng MZhou ZZhang MLiu GZeng D(2024)A Two-Way Active Contour Model for Incomplete Contour SegmentationCircuits, Systems, and Signal Processing10.1007/s00034-024-02754-743:10(6437-6458)Online publication date: 1-Oct-2024
https://dl.acm.org/doi/10.1007/s00034-024-02754-7
Yang CWeng GChen Y(2023)Active contour model based on local Kullback–Leibler divergence for fast image segmentationEngineering Applications of Artificial Intelligence10.1016/j.engappai.2023.106472123:PCOnline publication date: 1-Aug-2023
https://dl.acm.org/doi/10.1016/j.engappai.2023.106472
Andrikos IStefanou KBellos CStergios GAlchera ELocatelli IAlfano M(2023)EDIT SoftwareComputer Methods and Programs in Biomedicine10.1016/j.cmpb.2023.107448232:COnline publication date: 1-Apr-2023
https://dl.acm.org/doi/10.1016/j.cmpb.2023.107448
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A geometric model for active contours in image processing
1. Computing methodologies
  1. Computer graphics
2. Mathematics of computing
  1. Mathematical analysis
    1. Differential equations

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Published In

cover image Numerische Mathematik

Numerische Mathematik Volume 66, Issue 1

December 1993

524 pages

ISSN:0029-599X

Issue’s Table of Contents

Copyright © Copyright © 1994 Springer-Verlag.

Publisher

Springer-Verlag

Berlin, Heidelberg

Publication History

Published: 01 December 1993

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Cited By

Deng MZhou ZZhang MLiu GZeng D(2024)A Two-Way Active Contour Model for Incomplete Contour SegmentationCircuits, Systems, and Signal Processing10.1007/s00034-024-02754-743:10(6437-6458)Online publication date: 1-Oct-2024
https://dl.acm.org/doi/10.1007/s00034-024-02754-7
Yang CWeng GChen Y(2023)Active contour model based on local Kullback–Leibler divergence for fast image segmentationEngineering Applications of Artificial Intelligence10.1016/j.engappai.2023.106472123:PCOnline publication date: 1-Aug-2023
https://dl.acm.org/doi/10.1016/j.engappai.2023.106472
Andrikos IStefanou KBellos CStergios GAlchera ELocatelli IAlfano M(2023)EDIT SoftwareComputer Methods and Programs in Biomedicine10.1016/j.cmpb.2023.107448232:COnline publication date: 1-Apr-2023
https://dl.acm.org/doi/10.1016/j.cmpb.2023.107448
Yu JWellmann FVirgo Svon Domarus MJiang MSchmatz JLeibe B(2023)Superpixel segmentations for thin sectionsComputers & Geosciences10.1016/j.cageo.2022.105232170:COnline publication date: 1-Jan-2023
https://dl.acm.org/doi/10.1016/j.cageo.2022.105232
Narayan VFaiz MMall PSrivastava S(2023)A Comprehensive Review of Various Approach for Medical Image Segmentation and Disease PredictionWireless Personal Communications: An International Journal10.1007/s11277-023-10682-z132:3(1819-1848)Online publication date: 8-Aug-2023
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Hadjadj Z(2023)A cooperative framework for automated segmentation of tumors in brain MRI imagesMultimedia Tools and Applications10.1007/s11042-023-14736-z82:26(41381-41404)Online publication date: 29-Mar-2023
https://dl.acm.org/doi/10.1007/s11042-023-14736-z
Keatmanee CThongvigitmanee SChaumrattanakul UMakhanov S(2022)A Breast Cancer Contour Detection With Level Sets and SVM ModelInternational Journal of Knowledge and Systems Science10.4018/IJKSS.30547713:1(1-14)Online publication date: 2-Sep-2022
https://dl.acm.org/doi/10.4018/IJKSS.305477
Ge PChen YWang GWeng G(2022)A hybrid active contour model based on pre-fitting energy and adaptive functions for fast image segmentationPattern Recognition Letters10.1016/j.patrec.2022.04.025158:C(71-79)Online publication date: 1-Jun-2022
https://dl.acm.org/doi/10.1016/j.patrec.2022.04.025
Ge PChen YWang GWeng G(2022)An active contour model driven by adaptive local pre-fitting energy function based on Jeffreys divergence for image segmentationExpert Systems with Applications: An International Journal10.1016/j.eswa.2022.118493210:COnline publication date: 30-Dec-2022
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Kumar AJain S(2022)Deformable models for image segmentationComputers & Mathematics with Applications10.1016/j.camwa.2022.05.034119:C(288-311)Online publication date: 14-Jul-2022
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