An FPGA based coprocessor for GLCM and Haralick texture features and their application in prostate cancer classification

被引：52

作者：

Tahir, MA ^{[1
]}

Bouridane, A ^{[1
]}

Kurugollu, F ^{[1
]}

机构：

[1] Queens Univ Belfast, Sch Comp Sci, Belfast BT7 1NN, Antrim, North Ireland

来源：

ANALOG INTEGRATED CIRCUITS AND SIGNAL PROCESSING | 2005年 / 43卷 / 02期

关键词：

FPGAs; multispectral images; medical image classification; GLCM; Haralick texture features;

D O I：

10.1007/s10470-005-6793-2

中图分类号：

TP3 [计算技术、计算机技术];

学科分类号：

0812 ;

摘要：

Grey Level Co-occurrence Matrix (GLCM), one of the best known tool for texture analysis, estimates image properties related to second-order statistics. These image properties commonly known as Haralick texture features can be used for image classification, image segmentation, and remote sensing applications. However, their computations are highly intensive especially for very large images such as medical ones. Therefore, methods to accelerate their computations are highly desired. This paper proposes the use of programmable hardware to accelerate the calculation of GLCM and Haralick texture features. Further, as an example of the speedup offered by programmable logic, a multispectral computer vision system for automatic diagnosis of prostatic cancer has been implemented. The performance is then compared against a microprocessor based solution.

引用

页码：205 / 215

页数：11

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