Date of Award
2020
Publisher
North Dakota State University
Document Type
Dissertation
Degree Awarded
Doctor of Philosophy (PhD)
Department
Electrical and Computer Engineering
College
Engineering
Faculty Advisor
Smith, Scott
Description
The research described in this doctoral dissertation focuses on three main topics:1) performance optimization of the Viola-Jones Algorithm (VJA) for red-winged blackbird (Agelaius phoeniceus) detection, 2) further increasing performance of an already optimized asynchronous Multiply and Accumulate (MAC) unit, and 3) development of a framework to differentiate between lodging and non-lodging areas of a field from visible and multispectral aerial drone images. The first topic explores VJA rotational robustness, since VJA object detection is inherently not invariant to in-plane object rotation. An efficient method to detect rotated blackbirds is developed, which provides a balance between detection accuracy and computational cost. The second topic further optimizes a previously developed high-speed asynchronous 72+32×32 MAC, which was the fastest in the literature, resulting in a speedup of 1.36 while also decreasing area by 8%. The third topic develops a model to distinguish lodging from non-lodging plots, using a Support Vector Machine model trained with color, texture, Normalized Difference Vegetation Index (NDVI), and height features. The model prediction accuracy is around 90%, indicating good performance in distinguishing lodging from non-lodging plots.
Recommended Citation
Jalil, Nauman, "Development of Performance Optimized Rotation Tolerant Viola-Jones Based Blackbird Detection, a Throughput Optimized Asynchronous Mac Implementation, and Automated Wheat Lodging Estimation" (2020). Electrical and Computer Engineering. 43.
https://digitalcommons.ndsu.edu/elec-comp-eng/43
Rights
NDSU policy 190.6.2
Rights Link
https://www.ndsu.edu/fileadmin/policy/190.pdf
Handle Identifier
https://hdl.handle.net/10365/31812