Autonomous Camera Alignment System
The most critical step in the process of identification or verification, using iris or facial recognition is the image capturing stage. A high quality image contains more accurate data about the features in an image. In iris or facial recognition system the rate of success depends on the quality...
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| Main Author: | |
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| Format: | Final Year Project |
| Language: | English |
| Published: |
2017
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| Online Access: | http://utpedia.utp.edu.my/19075/1/06.%2017737_Dissertation.pdf http://utpedia.utp.edu.my/19075/ |
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| Summary: | The most critical step in the process of identification or verification, using iris or facial
recognition is the image capturing stage. A high quality image contains more accurate
data about the features in an image. In iris or facial recognition system the rate of
success depends on the quality and the angle of the camera when capturing the image.
The highest rate of success in verification or identification is achieved when a high
resolution picture is taken, with the camera positioned exactly in front of the subject’s
face, as demonstrated by some of the previous studies done on the topic. Thus, a camera
alignment system is required for situations where the subject might move his/her head.
The proposed camera alignment system is consist of 2 independent arms that can move
to different coordinates in one plane. The subject’s face will first be detected by using
the Ada-boost algorithm with Haar cascades, and the width and height of the face will
then be translated from pixel to millimeter. The final coordinate of the face can be
estimated from the width and the height of the face. Based on the current angle of the
arms and the angle that will get the arms to the final position, the arms will be moved to
a specific angle. This system requires a powerful embedded platform. Thus, it is fully
integrated on a Raspberry Pi. |
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