Inplace 2D matching in compressed images

Amihood Amir, Gad M. Landau, Dina Sokol

Research output: Contribution to conferencePaperpeer-review


The compressed matching problem, defined in [1] is the problem of finding all occurrences of a pattern in a compressed text. In this paper we discuss the 2-dimensional compressed matching problem in Lempel-Ziv compressed images. Given a pattern of (uncompressed) size m × m, and a text of (uncompressed) size n × n, both in 2D-LZ compressed form, our algorithms finds all occurrences of P in T. The algorithm is strongly inplace, that is, the amount of extra space used is proportional to the best possible compression of a pattern of size m3. The best compression that the 2D-LZ technique can obtain for a file of size m2 is O(m). The time for performing the search is O(n2) and the preprocessing time is O(m3). Our algorithm is general in the sense that it can be used for any 2D compression which can sequentially decompressed in small space.

Original languageEnglish
Number of pages10
StatePublished - 2003
EventConfiguralble Computing: Technology and Applications - Boston, MA, United States
Duration: 2 Nov 19983 Nov 1998


ConferenceConfiguralble Computing: Technology and Applications
Country/TerritoryUnited States
CityBoston, MA

Bibliographical note

Funding Information:
* Corresponding author. E-mail addresses: (A. Amir), (G.M. Landau), (D. Sokol). 1 Partially supported by NSF grant CCR-01-04494 and ISF grant 282/01. Part of this work was done when the author was at AT&T Labs-Research, Shannon Laboratory. 2 Partially supported by NSF grant CCR-0104307, by NATO Science Programme grant PST.CLG.977017, by the Israel Science Foundation grant 282/01, by the FIRST Foundation of the Israel Academy of Science and Humanities, and by IBM Faculty Partnership Award. 3 Partially supported by an Israel Ministry of Industry and Commerce Magnet grant (KITE) and an AT&T travel grant.

ASJC Scopus subject areas

  • Software
  • General Mathematics


Dive into the research topics of 'Inplace 2D matching in compressed images'. Together they form a unique fingerprint.

Cite this