SISFOTENIKA
Vol 11, No 2 (2021): SISFOTENIKA

Implementation of Deep Learning on Number Recognition in Sign Language

Fini Keni Celsia (Fakultas Ilmu Komputer, Universitas Klabat)
Green Arther Sandag (Universitas Klabat)



Article Info

Publish Date
22 Apr 2021

Abstract

Measuring the wound area in diabetics is still using a manual way with a wound ruler. Whereas the ruler affixed to the wound will become a contaminated agent that can transmit the infection to other recipients. Digital measurement methods are needed to solve the problem. However, clarifying the boundaries between the wound and the skin requires carefulness and high accuracy. For this reason, it has needed an imaging method that can do segmentation between the wound and the skin boundary for diabetic patients based on digital, called digital planimetry. This study uses a masking contour image processing algorithm from the Hue, Saturation, Value (HSV), Then doing iteration five times and gamma filter. So the result of segmentation is formed. This study concludes that the segmentation with this method has not been able to perform the segment properly, and it requires more masking values, but the results of the 5th iteration got a minor error, which is 0.002%. The digital imaging carried out in this study could be developed to be a digital-based diabetic patient wound measurement tool.

Copyrights © 2021






Journal Info

Abbrev

st

Publisher

Subject

Computer Science & IT

Description

Jurnal Ilmiah SISFOTENIKA diterbitkan oleh LPPM STMIK Pontianak dan IndoCEISS. Frekuensi Terbit Tengah Tahunan (2 kali dalam setahun, yaitu bulan Januari dan Juli). Topik yang akan dipublikasikan oleh jurnal SISFOTENIKA berhubungan dengan teknologi informasi, komunikasi dan komputer yang berbentuk ...