A Parallel Implementation of 4-Dimensional Haralick Texture Analysis for Disk-Resident Image Datasets

Authors:
Brent Woods;Bradley Clymer;Joel Saltz;Tahsin Kurc
Affiliations:
Ohio State University;Ohio State University;Ohio State University;Ohio State University
Venue:
Proceedings of the 2004 ACM/IEEE conference on Supercomputing
Year:
2004

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Abstract

Texture analysis is one possible method to detect features in biomedical images. During texture analysis, texture related information is found by examining local variations in image brightness. 4-dimensional (4D) Haralick texture analysis is a method that extracts local variations along space and time dimensions and represents them as a collection of fourteen statistical parameters. However, the application of the 4D Haralick method on large time-dependent 2D and 3D image datasets is hindered by computation and memory requirements. This paper presents a parallel implementation of 4D Haralick texture analysis on PC clusters. We present a performance evaluation of our implementation on a cluster of PCs. Our results show that good performance can be achieved for this application via combined use of task- and data-parallelism.