An FPGA-based architecture for real time image feature extraction

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.