Projects:2017s1-110 ‘Real-Time’ FPGA Based Object Recognition & Threat Detection in Hardware

2017-03-30T08:53:44Z

A1667956: inital wiki entry.

== '''110 ‘Real-Time’ FPGA Based Object Recognition & Threat Detection in Hardware''' ==

Project sponsored by elmTEK in concert with DSTG

;'''Students:'''
: Aaron Panella
: Stephen La Vista

;'''Supervisor:'''
: Danny Gibbins
;'''Co-supervisor:'''
: Braden Phillips

'''Description:'''
Next generation platforms of the Australian Army future land force expect a level of threat warning and situational
awareness comparative to that enjoyed by the Air and Sea domains, whilst demanding significantly reduced size,
weight, power and expense. In collaboration with the Defence Science & Technology Group, elmTEK is investigating
the trade-off in performance associated with low cost sensing for Electronic Warfare applications, whilst maintaining
the sensor performance to detect and classify incoming threats and augment situational awareness to crew.
This project will continue the work of elmTEK interns over the summer by building threat detection and object
recognition modules onto the current Image Processing Framework.
FPGAs are an exciting technology that are becoming increasingly popular for applications with high volumes of data,
due to their ability to compute and process in parallel. This is a distinct advantage over conventional processors.
Students will perform research into real-time image processing with FPGAs, efficient hardware architectures for FPGAs,
performing mathematical operations efficiently in hardware and proper memory and clock usage for hardware
architectures

;'''Work Breakdown'''
:Both students will work on hardware/framework changes. Image Registration will primarily be done by one student, with the other assisting, as a means to achieve image stabilisation. Threat Detection will be done by the other student.

Projects - User contributions [en]

Projects:2017s1-110 ‘Real-Time’ FPGA Based Object Recognition & Threat Detection in Hardware