Theses and Dissertations
Issuing Body
Mississippi State University
Advisor
Ball, John E.
Committee Member
Archibald, Christopher
Committee Member
Gurbuz, Ali
Committee Member
Fowler, James E.
Date of Degree
8-9-2019
Document Type
Graduate Thesis - Open Access
Major
Electrical and Computer Engineering
Degree Name
Master of Science
College
James Worth Bagley College of Engineering
Department
Department of Electrical and Computer Engineering
Abstract
Many image processing algorithms exist that can accurately detect humans and other objects such as vehicles and animals. Many of these algorithms require large amounts of processing often requiring hardware acceleration with powerful central processing units (CPUs), graphics processing units (GPUs), field programmable gate arrays (FPGAs), etc. Implementing an algorithm that can detect objects such as humans at longer ranges makes these hardware requirements even more strenuous as the numbers of pixels necessary to detect objects at both close ranges and long ranges is greatly increased. Comparing the performance of different low-power implementations can be used to determine a trade-off between performance and power. An image differencing algorithm is proposed along with selected low-power hardware that is capable of detected humans at ranges of 500 m. Multiple versions of the detection algorithm are implemented on the selected hardware and compared for run-time performance on a low-power system.
URI
https://hdl.handle.net/11668/14484
Recommended Citation
Merchant, Caleb, "Low-power high-resolution image detection" (2019). Theses and Dissertations. 2979.
https://scholarsjunction.msstate.edu/td/2979
Comments
object detection||image detection||low-power||long-range||high-resolution||image differencing||frame differencing||morphology||multi-threading||hardware acceleration||ARM||Vivante||NXP||GPU||CPU