Testing Connectedness of Images

We investigate algorithms for testing whether an image is connected. Given a proximity parameter ϵ ∈ ( 0 , 1 ) and query access to a black-and-white image represented by an n × n matrix of Boolean pixel values, a (1-sided error) connectedness tester accepts if the image is connected and rejects with...

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Vydané v:Algorithmica Ročník 86; číslo 11; s. 3496 - 3517
Hlavní autori: Berman, Piotr, Murzabulatov, Meiram, Raskhodnikova, Sofya, Ristache, Dragos-Florian
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: New York Springer US 01.11.2024
Springer Nature B.V
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Abstract We investigate algorithms for testing whether an image is connected. Given a proximity parameter ϵ ∈ ( 0 , 1 ) and query access to a black-and-white image represented by an n × n matrix of Boolean pixel values, a (1-sided error) connectedness tester accepts if the image is connected and rejects with probability at least 2/3 if the image is ϵ -far from connected. We show that connectedness can be tested nonadaptively with O ( 1 ϵ 2 ) queries and adaptively with O ( 1 ϵ 3 / 2 log 1 ϵ ) queries. The best connectedness tester to date, by Berman, Raskhodnikova, and Yaroslavtsev (STOC 2014) had query complexity O ( 1 ϵ 2 log 1 ϵ ) and was adaptive. We also prove that every nonadaptive, 1-sided error tester for connectedness must make Ω ( 1 ϵ log 1 ϵ ) queries.
AbstractList We investigate algorithms for testing whether an image is connected. Given a proximity parameter ϵ∈(0,1) and query access to a black-and-white image represented by an n×n matrix of Boolean pixel values, a (1-sided error) connectedness tester accepts if the image is connected and rejects with probability at least 2/3 if the image is ϵ-far from connected. We show that connectedness can be tested nonadaptively with O(1ϵ2) queries and adaptively with O(1ϵ3/2log1ϵ) queries. The best connectedness tester to date, by Berman, Raskhodnikova, and Yaroslavtsev (STOC 2014) had query complexity O(1ϵ2log1ϵ) and was adaptive. We also prove that every nonadaptive, 1-sided error tester for connectedness must make Ω(1ϵlog1ϵ) queries.
We investigate algorithms for testing whether an image is connected. Given a proximity parameter ϵ ∈ ( 0 , 1 ) and query access to a black-and-white image represented by an n × n matrix of Boolean pixel values, a (1-sided error) connectedness tester accepts if the image is connected and rejects with probability at least 2/3 if the image is ϵ -far from connected. We show that connectedness can be tested nonadaptively with O ( 1 ϵ 2 ) queries and adaptively with O ( 1 ϵ 3 / 2 log 1 ϵ ) queries. The best connectedness tester to date, by Berman, Raskhodnikova, and Yaroslavtsev (STOC 2014) had query complexity O ( 1 ϵ 2 log 1 ϵ ) and was adaptive. We also prove that every nonadaptive, 1-sided error tester for connectedness must make Ω ( 1 ϵ log 1 ϵ ) queries.
Author Murzabulatov, Meiram
Raskhodnikova, Sofya
Ristache, Dragos-Florian
Berman, Piotr
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Cites_doi 10.1145/3531527
10.1109/TPAMI.2010.165
10.1002/rsa.20797
10.1007/s00493-007-2154-3
10.1109/FOCS.2017.83
10.1145/2591796.2591887
10.1109/CVPR.2013.302
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10.1137/S0097539702403244
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10.1137/S0097539793255151
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References Berman, P., Murzabulatov, M., Raskhodnikova, S., Ristache, D.: Testing connectedness of images. In: Megow, N., Smith, A.D. (eds.) Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques, APPROX/RANDOM 2023, September 11–13, 2023, Atlanta, Georgia, USA, volume 275 of LIPIcs, pp. 66:1–66:15. Schloss Dagstuhl - Leibniz-Zentrum für Informatik (2023)
MinskyMPapertSAPerceptrons: An Introduction to Computational Geometry2017CambridgeThe MIT Press10.7551/mitpress/11301.001.0001
Murzabulatov, M.: Testing Geometric Properties of Two-Dimensional Figures and Images. PhD thesis, The Pennsylvania State University (2017)
BerenbrinkPKrayenhoffBMallmann-TrennFEstimating the number of connected components in sublinear timeInf. Process. Lett.201411411639642323091310.1016/j.ipl.2014.05.008
LeviAPallavoorRKSRaskhodnikovaSVarmaNErasure-resilient sublinear-time graph algorithmsACM Trans. Comput. Theory20221411:11:22441586510.1145/3488250
ParnasMRonDTesting the diameter of graphsRandom Struct. Algorithms2002202165183188443110.1002/rsa.10013
BermanPMurzabulatovMRaskhodnikovaSThe power and limitations of uniform samples in testing properties of figuresAlgorithmica201981312471266391798610.1007/s00453-018-0467-9
Raskhodnikova, S.: Property testing : theory and applications. PhD thesis, Massachusetts Institute of Technology (2003)
Korman, S., Reichman, D., Tsur, G.: Tight approximation of image matching. CoRR, arXiv:1111.1713 (2011)
RubinfeldRSudanMRobust characterizations of polynomials with applications to program testingSIAM J. Comput.1996252252271137930010.1137/S0097539793255151
Yao, A.C.: Probabilistic computation, towards a unified measure of complexity. In: Proceedings of the Eighteenth Annual Symposium on Foundations of Computer Science, pp. 222–227 (1977)
BermanPMurzabulatovMRaskhodnikovaSTolerant testers of image propertiesACM Trans. Algorithms2022184139450981210.1145/3531527
ChazelleBRubinfeldRTrevisanLApproximating the minimum spanning tree weight in sublinear timeSIAM J. Comput.20053413701379216574510.1137/S0097539702403244
Korman, S., Reichman, D., Tsur, G., Avidan, S.: Fast-match: Fast affine template matching. In: CVPR, pp. 2331–2338. IEEE (2013)
KleinerIKerenDNewmanIBen-ZwiOApplying property testing to an image partitioning problemIEEE Trans. Pattern Anal. Mach. Intell.201133225626510.1109/TPAMI.2010.165
Ben-Eliezer, O., Fischer, E.: Earthmover resilience and testing in ordered structures. In: Servedio, R.A. (ed.) 33rd Computational Complexity Conference, CCC 2018, June 22–24, 2018, San Diego, CA, USA, volume 102 of LIPIcs, pp. 18:1–18:35. Schloss Dagstuhl - Leibniz-Zentrum für Informatik (2018)
Berman, P., Raskhodnikova, S., Yaroslavtsev, G.: Lp\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$L_p$$\end{document}-testing. In: Shmoys, D.B. (ed.) Symposium on Theory of Computing, STOC 2014, New York, NY, USA, May 31–June 03, 2014, pp. 164–173. ACM (2014)
GoldreichORonDProperty testing in bounded degree graphsAlgorithmica2002322302343186951410.1007/s00453-001-0078-7
RonDTsurGTesting properties of sparse imagesACM Trans. Algorithms201410417:117:52325450510.1145/2635806
Ben-Eliezer, O., Korman, S., Reichman, D.: Deleting and testing forbidden patterns in multi-dimensional arrays. In: Chatzigiannakis, I., Indyk, P., Kuhn, F., Muscholl, A. (eds.) 44th International Colloquium on Automata, Languages, and Programming, ICALP 2017, July 10–14, 2017, Warsaw, Poland, volume 80 of LIPIcs, pp. 9:1–9:14. Schloss Dagstuhl - Leibniz-Zentrum für Informatik (2017)
Alon, N., Ben-Eliezer, O., Fischer, E.: Testing hereditary properties of ordered graphs and matrices. In: Umans, C. (ed.) 58th IEEE Annual Symposium on Foundations of Computer Science, FOCS 2017, Berkeley, CA, USA, October 15–17, 2017, pp. 848–858. IEEE Computer Society (2017)
GoldreichOGoldwasserSRonDProperty testing and its connection to learning and approximationJ. ACM1998454653750167509910.1145/285055.285060
FischerENewmanITesting of matrix-poset propertiesCombinatorica2007273293327234581210.1007/s00493-007-2154-3
ParalPChatterjeeARakshitAVision sensor-based shoe detection for human tracking in a human-robot coexisting environment: a photometric invariant approach using dbscan algorithmIEEE Sens. J.201919124549455910.1109/JSEN.2019.2897989
BermanPMurzabulatovMRaskhodnikovaSTesting figures under the uniform distributionRandom Struct. Algorithms2019543413443393877410.1002/rsa.20797
Raskhodnikova, S.: Approximate testing of visual properties. In: Arora, S., Jansen, K., Rolim, J.D.P., Sahai, A. (eds.) RANDOM-APPROX, volume 2764 of Lecture Notes in Computer Science, pp. 370–381. Springer (2003)
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– reference: Berman, P., Murzabulatov, M., Raskhodnikova, S., Ristache, D.: Testing connectedness of images. In: Megow, N., Smith, A.D. (eds.) Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques, APPROX/RANDOM 2023, September 11–13, 2023, Atlanta, Georgia, USA, volume 275 of LIPIcs, pp. 66:1–66:15. Schloss Dagstuhl - Leibniz-Zentrum für Informatik (2023)
– reference: Raskhodnikova, S.: Approximate testing of visual properties. In: Arora, S., Jansen, K., Rolim, J.D.P., Sahai, A. (eds.) RANDOM-APPROX, volume 2764 of Lecture Notes in Computer Science, pp. 370–381. Springer (2003)
– reference: Raskhodnikova, S.: Property testing : theory and applications. PhD thesis, Massachusetts Institute of Technology (2003)
– reference: Korman, S., Reichman, D., Tsur, G.: Tight approximation of image matching. CoRR, arXiv:1111.1713 (2011)
– reference: GoldreichORonDProperty testing in bounded degree graphsAlgorithmica2002322302343186951410.1007/s00453-001-0078-7
– reference: BerenbrinkPKrayenhoffBMallmann-TrennFEstimating the number of connected components in sublinear timeInf. Process. Lett.201411411639642323091310.1016/j.ipl.2014.05.008
– reference: RonDTsurGTesting properties of sparse imagesACM Trans. Algorithms201410417:117:52325450510.1145/2635806
– reference: ChazelleBRubinfeldRTrevisanLApproximating the minimum spanning tree weight in sublinear timeSIAM J. Comput.20053413701379216574510.1137/S0097539702403244
– reference: Murzabulatov, M.: Testing Geometric Properties of Two-Dimensional Figures and Images. PhD thesis, The Pennsylvania State University (2017)
– reference: Korman, S., Reichman, D., Tsur, G., Avidan, S.: Fast-match: Fast affine template matching. In: CVPR, pp. 2331–2338. IEEE (2013)
– reference: Ben-Eliezer, O., Korman, S., Reichman, D.: Deleting and testing forbidden patterns in multi-dimensional arrays. In: Chatzigiannakis, I., Indyk, P., Kuhn, F., Muscholl, A. (eds.) 44th International Colloquium on Automata, Languages, and Programming, ICALP 2017, July 10–14, 2017, Warsaw, Poland, volume 80 of LIPIcs, pp. 9:1–9:14. Schloss Dagstuhl - Leibniz-Zentrum für Informatik (2017)
– reference: BermanPMurzabulatovMRaskhodnikovaSTesting figures under the uniform distributionRandom Struct. Algorithms2019543413443393877410.1002/rsa.20797
– reference: Yao, A.C.: Probabilistic computation, towards a unified measure of complexity. In: Proceedings of the Eighteenth Annual Symposium on Foundations of Computer Science, pp. 222–227 (1977)
– reference: RubinfeldRSudanMRobust characterizations of polynomials with applications to program testingSIAM J. Comput.1996252252271137930010.1137/S0097539793255151
– reference: ParnasMRonDTesting the diameter of graphsRandom Struct. Algorithms2002202165183188443110.1002/rsa.10013
– reference: FischerENewmanITesting of matrix-poset propertiesCombinatorica2007273293327234581210.1007/s00493-007-2154-3
– reference: Alon, N., Ben-Eliezer, O., Fischer, E.: Testing hereditary properties of ordered graphs and matrices. In: Umans, C. (ed.) 58th IEEE Annual Symposium on Foundations of Computer Science, FOCS 2017, Berkeley, CA, USA, October 15–17, 2017, pp. 848–858. IEEE Computer Society (2017)
– reference: KleinerIKerenDNewmanIBen-ZwiOApplying property testing to an image partitioning problemIEEE Trans. Pattern Anal. Mach. Intell.201133225626510.1109/TPAMI.2010.165
– reference: LeviAPallavoorRKSRaskhodnikovaSVarmaNErasure-resilient sublinear-time graph algorithmsACM Trans. Comput. Theory20221411:11:22441586510.1145/3488250
– reference: ParalPChatterjeeARakshitAVision sensor-based shoe detection for human tracking in a human-robot coexisting environment: a photometric invariant approach using dbscan algorithmIEEE Sens. J.201919124549455910.1109/JSEN.2019.2897989
– reference: Ben-Eliezer, O., Fischer, E.: Earthmover resilience and testing in ordered structures. In: Servedio, R.A. (ed.) 33rd Computational Complexity Conference, CCC 2018, June 22–24, 2018, San Diego, CA, USA, volume 102 of LIPIcs, pp. 18:1–18:35. Schloss Dagstuhl - Leibniz-Zentrum für Informatik (2018)
– reference: GoldreichOGoldwasserSRonDProperty testing and its connection to learning and approximationJ. ACM1998454653750167509910.1145/285055.285060
– reference: Berman, P., Raskhodnikova, S., Yaroslavtsev, G.: Lp\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$L_p$$\end{document}-testing. In: Shmoys, D.B. (ed.) Symposium on Theory of Computing, STOC 2014, New York, NY, USA, May 31–June 03, 2014, pp. 164–173. ACM (2014)
– reference: MinskyMPapertSAPerceptrons: An Introduction to Computational Geometry2017CambridgeThe MIT Press10.7551/mitpress/11301.001.0001
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Snippet We investigate algorithms for testing whether an image is connected. Given a proximity parameter ϵ ∈ ( 0 , 1 ) and query access to a black-and-white image...
We investigate algorithms for testing whether an image is connected. Given a proximity parameter ϵ∈(0,1) and query access to a black-and-white image...
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SubjectTerms Algorithm Analysis and Problem Complexity
Algorithms
Computer Science
Computer Systems Organization and Communication Networks
Data Structures and Information Theory
Mathematics of Computing
Queries
Theory of Computation
Title Testing Connectedness of Images
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