High Performance Automatic Target Recognition
| dc.contributor.advisor | Adugna, Eneyew | |
| dc.contributor.author | Tadesse, Misiker | |
| dc.date.accessioned | 2018-07-11T11:49:06Z | |
| dc.date.accessioned | 2023-11-04T15:14:38Z | |
| dc.date.available | 2018-07-11T11:49:06Z | |
| dc.date.available | 2023-11-04T15:14:38Z | |
| dc.date.issued | 2012-10 | |
| dc.description.abstract | Designing a vision system, which was motivated by that of the human eye, has been done since the introduction of digital computing devices. Due to its abundant applications, this area is a hot topic in the industry. Its computational complexity hinders it from the required accuracy and flexibility achievable by these systems. The evolution of processing technology has given to the birth of parallel processing units such as Graphics Processing Unit (GPU) and Field Programmable Gate Array (FPGA). Using these parallel processing units Data Intensive applications can be done in parallel to get a performance speedup with lower implementation cost, unlike Application Specific Integrated Circuits (ASICs). In this thesis, a real-time Automatic Target Recognition system having the ability of detection, identification and tracking of pre-specified targets even with bad visual artifacts that could originate from lightning conditions, environmental conditions or other noise generating circumstances is developed. This thesis work investigates an improved combination of detection and recognition algorithms to reach a better solution to the problem of target detection and recognition while aiming to fit the design of a minimal system. For each algorithm involved the theoretical background is investigated and a detailed description of the realization is given followed by an analysis of both achievements and short comings of the design. A speed up of 2.4 is achieved, by using a non-preeminent GPU, over brute force implementations. | en_US |
| dc.description.sponsorship | Addis Ababa University | en_US |
| dc.identifier.uri | http://etd.aau.edu.et/handle/123456789/8033 | |
| dc.language.iso | en | en_US |
| dc.publisher | Addis Ababa University | en_US |
| dc.subject | Microelectronics Engineering | en_US |
| dc.title | High Performance Automatic Target Recognition | en_US |
| dc.type | Thesis | en_US |