An FPGA-Based Architecture for Real Time Image Feature Extraction

Authors:
D. G. Bariamis;D. K. Iakovidis;D. E. Maroulis;S. A. Karkanis
Affiliations:
University of Athens, Greece;University of Athens, Greece;University of Athens, Greece;Technological Educational Institute of Lamia, Greece
Venue:
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 1 - Volume 01
Year:
2004

Citing 0
Cited 6

Design of a systolic-pipelined architecture for real-time enhancement of color video stream based on an illuminance-reflectance model

Integration, the VLSI Journal
FPGA-based System for Real-Time Video Texture Analysis

Journal of Signal Processing Systems
Design of a high performance architecture for real-time enhancement of video stream captured in extremely low lighting environment

Microprocessors & Microsystems
A scalable and embedded FPGA architecture for efficient computation of grey level co-occurrence matrices and Haralick textures features

Microprocessors & Microsystems
Parallel implementation of Gray Level Co-occurrence Matrices and Haralick texture features on cell architecture

The Journal of Supercomputing
High performance implementation of texture features extraction algorithms using FPGA architecture

Journal of Real-Time Image Processing

Quantified Score

Hi-index	0.00

Visualization

Abstract

We propose a novel FPGA-based architecture for the extraction of four texture features using Gray Level Cooccurrence Matrix (GLCM) analysis. These features are angular second moment, correlation, inverse difference moment, and entropy. The proposed architecture consists of a hardware and a software module. The hardware module is implemented on Xilinx Virtex-E V2000 FPGA using VHDL. It calculates many GLCMs and GLCM integer features in parallel. The software retrieves the feature vectors calculated in hardware and performs complementary computations. The architecture was evaluated using standard grayscale images and video clips. The results show that it can be efficiently used in realtime pattern recognition applications.