2. HaVIRAS - Why FPGA
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Transcript of 2. HaVIRAS - Why FPGA
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PolitecnicodiMilanoDipartimentodiElettronica,InformazioneeBioingegneria(DEIB)
XOHW16Meeting
MarcoBottinoPierandreaCancian
GuidoWalterDiDonato
WHYFPGA2/8
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The target
● A biometric feature extractor
for an identification system
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Acquisition
Preprocessing &&
ROI Individuation
Processing
Feature extraction
Storage
Matching &&
Decision
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The target
● A biometric feature extractor
for an identification system:
Safe
2
Acquisition
Preprocessing &&
ROI Individuation
Processing
Feature extraction
Matching &&
Decision
Storage
Encrypting
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The target
● A biometric feature extractor
for an identification system:
Safe
Embedded
SoC
Matching &&
Decision
Storage
Acquisition
Preprocessing &&
ROI Individuation
Processing
Feature extraction
Encrypting
2
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The target
● A biometric feature extractor
for an identification system:
Safe
Embedded
yet fast!
2
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Some of the involved processes
are computationally cumbersome,
such as:
● Median Filter
● Local thresholding
● Skeletonization
The problem
Tome_BIOSIG_2015
DOI: 10.1109/ICMA.2005.1626888 · IEEE Xplore
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The problem
Tome_BIOSIG_2015
http://images.clipartpanda.com/gary-the-snail-clipart-gary002.gif
Too slow in SW on an embedded system!
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Some of the involved processes
are computationally cumbersome,
such as:
● Median Filter
● Local thresholding
● Skeletonization
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HW acceleration to reduce computation time:
The solution
FPGA
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From “Personal Verification using Finger Vein Biometrics in FPGA-based System-on-Chip”. Available @ www.emo.org.tr/ekler/41b718e81e5a762_ek.pdf
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HW acceleration to reduce computation time:
The solution
FPGA
Embedded
+=
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TM
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[email protected] [email protected] [email protected]
https://www.facebook.com/HaVIRAS2016/
https://twitter.com/HaVIRAS_NECST
HandVesselsInfraRedAuthenticationSystem
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