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

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 timedependent 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.

• Type: Conference
• Year: 2004
• Where: SC
• Authors: Brent Woods, Bradley D. Clymer, Joel H. Saltz, Tahsin M. Kurç
• Keywords: Applied Computing, Haralick Texture Analysis, Local Variations, SC 2004, Texture Analysis