Two Strategies to Speed up Connected Component LabelingAlgorithms

This paper presents two new strategies to speed up connectedcomponent labeling algorithms. The first strategy employs a decisiontreeto minimize the work performed in the scanning phase of connectedcomponent labeling algorithms. The second strategy uses a simplifiedunion-find data structure to represent the equivalence information amongthe labels. For 8-connected components in atwo-dimensional (2D) image,the first strategy reduces the number of neighboring pixels visited from4 to7/3 on average. In various tests, using a decision tree decreases thescanning time by a factor of about 2. The second strategy uses a compactrepresentation of the union-find data structure. This strategysignificantly speeds up the labeling algorithms. We prove analyticallythat a labeling algorithm with our simplified union-find structure hasthe same optimal theoretical time complexity as do the best labelingalgorithms. By extensive experimental measurements, we confirm theexpected performance characteristics of the new labeling algorithms anddemonstrate that they are faster than other optimal labelingalgorithms

Worst-case and Amortised Optimality in Union-Find (Extended Abstract)

We study the interplay between worst-case and amortised time bounds for the classic Disjoint Set Union problem (Union-Find). We ask whether it is possible to achieve optimal worst-case and amortised bounds simultaneously. Furthermore we would like to allow a tradeoff between the worst-case time for a query and for an update. We answer this question by first providing lower bounds for the possible worst-case time tradeoffs, as well as lower bounds which show where in this tradeoff range optimal amortised time is achievable. We then give an algorithm which tightly matches both lower bounds simultaneously. The lower bounds are provided in the cell-probe model as well as in the algebraic real-number RAM, and the upper bounds hold for a RAM with logarithmic word size and a modest instruction set. Our lower bounds show that for worst-case query and update time t q and t u respectively, one must have t q = 780 n= log t u ), and only for t q (m; n) can this tradeoff be achieved simultaneou..

Lower bound techniques for data structures

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2008.Includes bibliographical references (p. 135-143).We describe new techniques for proving lower bounds on data-structure problems, with the following broad consequences: * the first [omega](lg n) lower bound for any dynamic problem, improving on a bound that had been standing since 1989; * for static data structures, the first separation between linear and polynomial space. Specifically, for some problems that have constant query time when polynomial space is allowed, we can show [omega](lg n/ lg lg n) bounds when the space is O(n - polylog n). Using these techniques, we analyze a variety of central data-structure problems, and obtain improved lower bounds for the following: * the partial-sums problem (a fundamental application of augmented binary search trees); * the predecessor problem (which is equivalent to IP lookup in Internet routers); * dynamic trees and dynamic connectivity; * orthogonal range stabbing. * orthogonal range counting, and orthogonal range reporting; * the partial match problem (searching with wild-cards); * (1 + [epsilon])-approximate near neighbor on the hypercube; * approximate nearest neighbor in the l[infinity] metric. Our new techniques lead to surprisingly non-technical proofs. For several problems, we obtain simpler proofs for bounds that were already known.by Mihai Pǎtraşcu.Ph.D

LIPIcs, Volume 244, ESA 2022, Complete Volume

LIPIcs, Volume 244, ESA 2022, Complete Volum

Programming Languages and Systems

This open access book constitutes the proceedings of the 30th European Symposium on Programming, ESOP 2021, which was held during March 27 until April 1, 2021, as part of the European Joint Conferences on Theory and Practice of Software, ETAPS 2021. The conference was planned to take place in Luxembourg and changed to an online format due to the COVID-19 pandemic. The 24 papers included in this volume were carefully reviewed and selected from 79 submissions. They deal with fundamental issues in the specification, design, analysis, and implementation of programming languages and systems

LIPIcs, Volume 261, ICALP 2023, Complete Volume

LIPIcs, Volume 261, ICALP 2023, Complete Volum

LIPIcs, Volume 258, SoCG 2023, Complete Volume

LIPIcs, Volume 258, SoCG 2023, Complete Volum