Development and analysis of embedded face recognition system using Raspberry Pi
Human Face is the most visible part which can be used to recognize persons. There are many available systems for face recognition in the market, but they are bulky and expensive. The implementation of face recognition techniques in an embedded system is a very important aspect. This project involve...
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| Main Author: | |
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| Format: | Thesis |
| Language: | English |
| Published: |
Universiti Malaysia Perlis (UniMAP)
2019
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| Subjects: | |
| Online Access: | http://dspace.unimap.edu.my:80/xmlui/handle/123456789/61835 |
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| Summary: | Human Face is the most visible part which can be used to recognize persons. There are many available systems for face recognition in the market, but they are bulky and
expensive. The implementation of face recognition techniques in an embedded system is a very important aspect. This project involves design of a real-time, portable, low embedded cost face recognition system. Implementation and analysis of face
recognition techniques on an embedded system, the development phase consists of
Single Board Computer (SBC, Raspberry Pi (Model A) as process unite, and
GNU/Linux based Embedded Raspbian Operating system is used as application
development platform. This project focuses to apply the face recognition algorithm that
is suitable with Raspberry Pi (Model A) The proposed system is implemented using
ARM11 processor and inefficient memory on Raspberry Pi (Model A) board, to get an
acceptable performance of the system, the images are captured at resolution (320×240),
the system needs ≈ 2.1 sec to process the captured images, The performance of the
embedded system is done by evaluating detection time and recognition time (is 1.75 sec,
between 0.29 sec to 0.74 sec) respectively, together with CPU utilization and RAM
utilization (33%, 17.75%) for detection and (36.5%, 22%) for recognition. Results
obtained shows that the overall performance on the embedded system can be increased
when motion detection techniques is applied. |
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