Computing image texture features in parallel computers

Author

Sanz, Jorge L C

Author_Institution

IBM Almaden Res. Center, San Jose, CA, USA

Volume

76

Issue

3

fYear

1988

fDate

3/1/1988 12:00:00 AM

Firstpage

292

Lastpage

294

Abstract

The problem of computing image texture features in parallel computers is addressed. It is shown that R. Haralick´s texture measures (1973) are amenable to efficient implementation in certain fine-grained architectures. The main operation used to compute these features is the SEND, also called Random Access Write, command. This command is efficiently implemented in a number of computers, such as binary n -cubes, mesh-arrays, and some shared-memory systems. It is shown that the computation of gray-level dependency matrices requires random global communication patterns. This feature and the need for other standard local processing make the classification measures proposed by Haralick and his associates good candidates as benchmarks for parallel computer vision architectures

Keywords

computer vision; computerised picture processing; parallel architectures; Random Access Write; SEND; binary n-cubes; classification measures; computer vision architectures; fine-grained architectures; gray-level dependency matrices; image texture features; mesh-arrays; parallel computers; random global communication patterns; shared-memory systems; standard local processing; texture features; Broadcasting; Computer architecture; Computer vision; Concurrent computing; Global communication; Image analysis; Image processing; Image texture; Image texture analysis; Measurement standards; Parallel architectures; Time varying systems;

fLanguage

English

Journal_Title

Proceedings of the IEEE

Publisher

ieee

ISSN

0018-9219

Type

jour

DOI

10.1109/5.4411

Filename

4411