Accelerating Statistical Texture Analysis with an FPGA-DSP Hybrid Architecture
FCCM '01 Proceedings of the the 9th Annual IEEE Symposium on Field-Programmable Custom Computing Machines
Analog Integrated Circuits and Signal Processing
FPGA-based System for Real-Time Video Texture Analysis
Journal of Signal Processing Systems
Boosting for Image Interpretation by Using Natural Features
MICAI '08 Proceedings of the 2008 Seventh Mexican International Conference on Artificial Intelligence
DSD '09 Proceedings of the 2009 12th Euromicro Conference on Digital System Design, Architectures, Methods and Tools
CERMA '10 Proceedings of the 2010 IEEE Electronics, Robotics and Automotive Mechanics Conference
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This article presents an architecture based on FPGA for the calculation of texture attributes using an adequacy of the technique of sum and differences of histograms. The attributes calculated by this architecture will be used in a process of classification for identification of objects during the navigation of an autonomous robot of service. Because of that, the constraint of real-time execution plays an essential role during the architecture design. So, the architecture is designed to calculate 30 dense images with 6 different attributes of texture for 10 different displacements. Exploiting the reuse of operations in parallel on the FPGA and taking into account the requisites in the time of calculation, it is possible to use the resources in an efficient and optimised way in order to obtain an architecture with the best trade off between resources and the time of calculation. Thanks to the high performance of this architecture, it can be used in applications like medical diagnosis or target detection.