TY - JOUR
T1 - Image Enhancement Sputum Containing Mycobacterium Tuberculosis Using A Spatial Domain Filter
AU - Rachmad, Aeri
AU - Chamidah, Nur
AU - Rulaningtyas, Riries
N1 - Publisher Copyright:
© Published under licence by IOP Publishing Ltd.
PY - 2019/7/1
Y1 - 2019/7/1
N2 - Image enhancement sputum is needed to identify bacteria mycobacterium tuberculosis (TB). The number of TB bacteria in sputum images determines the severity of tuberculosis sufferers. In this paper, we study image enhancement sputum techniques by using spatial domain filter-based methods such as median filtering, Gaussian filtering, adaptive noise-removal filtering and bilateral filtering. These filtering techniques are used to overcome the problems when taking sputum images such as adjusting the focus of the lens, lighting and dirt that stick to the lens and on the slide glass. The obtained results for 100 data sputum images from this study are average means square error (MSE) of median filtering, Gaussian filtering, adaptive noise-removal filtering and bilateral filtering, i.e., 30.68, 17.10, 18.92 and 26.28, respectively. Also, average peak signal-to-noise ratio (PSNR) of them are 33.70 dB, 35.91 dB, 35.59 dB and 34.01 dB, respectively. The avarage computational time are 0.09 sec, 0.18 sec, 0.38 sec and 134 sec respectively.
AB - Image enhancement sputum is needed to identify bacteria mycobacterium tuberculosis (TB). The number of TB bacteria in sputum images determines the severity of tuberculosis sufferers. In this paper, we study image enhancement sputum techniques by using spatial domain filter-based methods such as median filtering, Gaussian filtering, adaptive noise-removal filtering and bilateral filtering. These filtering techniques are used to overcome the problems when taking sputum images such as adjusting the focus of the lens, lighting and dirt that stick to the lens and on the slide glass. The obtained results for 100 data sputum images from this study are average means square error (MSE) of median filtering, Gaussian filtering, adaptive noise-removal filtering and bilateral filtering, i.e., 30.68, 17.10, 18.92 and 26.28, respectively. Also, average peak signal-to-noise ratio (PSNR) of them are 33.70 dB, 35.91 dB, 35.59 dB and 34.01 dB, respectively. The avarage computational time are 0.09 sec, 0.18 sec, 0.38 sec and 134 sec respectively.
UR - http://www.scopus.com/inward/record.url?scp=85069499020&partnerID=8YFLogxK
U2 - 10.1088/1757-899X/546/5/052061
DO - 10.1088/1757-899X/546/5/052061
M3 - Conference article
AN - SCOPUS:85069499020
SN - 1757-8981
VL - 546
JO - IOP Conference Series: Materials Science and Engineering
JF - IOP Conference Series: Materials Science and Engineering
IS - 5
M1 - 052061
T2 - 9th Annual Basic Science International Conference 2019, BaSIC 2019
Y2 - 20 March 2019 through 21 March 2019
ER -