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En jämförelse av Eigenface- och Fisherface-metoden tillämpade i en Raspberry Pi 2
Jönköping University, School of Engineering, JTH, Computer and Electrical Engineering.
Jönköping University, School of Engineering, JTH, Computer and Electrical Engineering.
2016 (Swedish)Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesisAlternative title
A comparison between Eigenfaces and Fisherfaces implemented on a Raspberry Pi 2 (English)
Abstract [sv]

Syftet med rapporten är att visa möjligheten att använda Raspberry Pi 2 i ett ansiktsigenkänningssystem. Studien redogör för prestandaskillnader mellan Eigenface och Fisherfacemetoden.

Studieförfattarna har genomfört en experimentell studie enligt en kvantitativ metod där tester utgör empirin. Resultatet från testerna kommer presenteras genom diagram och påvisa möjligheten att använda Raspberry Pi 2 som hårdvara i ett ansiktsigenkänningssystem. Genom samma testutförande kommer skillnader mellan igenkänningsmetoderna att påvisas.

Studien visar att Raspberry Pi 2 är en lämplig kandidat att använda för mindre ansiktsigenkänningssystem. Vidare framgår det att Fisherface-metoden är det lämpligaste valet att använda vid implementation av systemet.

Abstract [en]

The purpose with this report is to demonstrate the possibility to use Raspberry Pi 2 as hardware in a face recognition system. The study will show performance differences regarding the Eigenface- and Fisherface-method.

To demonstrate the possibility the authors have done tests using an experimental study and quantitative method. To review the tests and to understand the result a qualitative literature review was taken.

The tests will be presented as graphs to show the possibility to use Raspberry Pi 2 as hardware in a face recognition system. The same goes for the comparison of the chosen algorithms. The work indicates that Raspberry Pi 2 is a possible candidate to use for smaller face recognition systems. There is also an indication that the Fisherface method is the better choice for face recognition.

Place, publisher, year, edition, pages
2016. , 31 p.
Keyword [en]
Face recognition, Eigenfaces, Fisherfaces, Raspberry Pi 2, Python, OpenCV, OpenCV_contrib, psutil.
Keyword [sv]
Ansiktsigenkänning, Eigenfaces, Fisherfaces, Raspberry Pi 2, Python, OpenCV, OpenCV_contrib, psutil
National Category
Embedded Systems
Identifiers
URN: urn:nbn:se:hj:diva-29795ISRN: JU-JTH-DTA-1-20160018OAI: oai:DiVA.org:hj-29795DiVA: diva2:921173
External cooperation
Combitech AB
Subject / course
JTH, Computer Engineering
Supervisors
Examiners
Available from: 2016-04-28 Created: 2016-04-19 Last updated: 2016-04-28Bibliographically approved

Open Access in DiVA

Examensarbete - Dag Dahl och Gustaf Sterne(925 kB)117 downloads
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