TELKOMNIKA Telecommunication, Computing, Electronics and Control
Automatic human ear detection approach using modified adaptive search window technique

TELKOMNIKA Telecommunication, Computing, Electronics and Control
Automatic human ear detection approach using modified adaptive search window technique

Adaptive search window
Automatic ear detection
Biometric
Computational time
Ear recognition

The human ear biometric recognition plays an important role in the forensics
specialty and has significant impact for biometrician scientists and researchers.
Actually, many ear recognition researches showed promised results, but some
issues such as manual detection process, efficiency and robustness aren’t
attained a certain level of maturity. Therefore, the enhancement developing
approaches still continuous to achieve limited successes. We propose an
efficient, reliable and simple automatic human ear detection approach. This
approach implement two stages: preprocessing and ear landmarks detection.
We utilized the image contrast, Laplace filter and Gaussian blurring techniques
to made enhancement on all images (increasing the contrast, reduce the noisy
and smoothing processes). After that, we highlighted the ear edges by using
the Sobel edge detector and determining the only white pixels of ear edges by
applying the image substation method. The improvement focused on using the
modified adaptive search window (ASW) to detect the ear region.
Furthermore, our approach is tested on Indian Institute of Technology (IIT)
Delhi standard ear biometric public dataset. Experimental results presented a
well average detection rate 96% for 493 image samples from 125 persons and
computational time almost ≈ 0.485 seconds which is evaluated with other
previous works.

Raad Ahmed Hadi, Loay Edwar George, Zainab Jawad Ahmed

http://journal.uad.ac.id/index.php/TELKOMNIKA

Oct 21, 2020

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