TY - JOUR
T1 - An age estimation method to panoramic radiographs from Indonesian individuals
AU - Yuniarti, Anny
AU - Arifin, Agus Zainal
AU - Wijaya, Arya Yudhi
AU - Khotimah, Wijayanti Nurul
PY - 2013/3
Y1 - 2013/3
N2 - Dental features can be considered as the best candidate feature for post-mortem identification. If ante-mortem data is unavailable, then forensic experts are needed for reducing the search space by creating post-mortem dental profiling. Age is one of important factors in dental profiling. Manual inspection of dental radiographs suffers from two drawbaks, i.e., intraobserver error and interobserver error. This paper proposed a semi-automatic system for age estimation. There are two phases in developing the proposed system, i.e., the modeling phase and the estimation phase. The modeling phase is the stage for deriving an estimation formula based on known data. In this paper, we use data taken from Javanese people. The estimation phase include the process of defining a Region of Interest (ROI), automatic length computation, and age estimation based on the derived modeling formula. Our experiments showed a promising result, i.e., an average absolute error of 5.2 years, compared to application of the Kvaal method to panoramic radiographs from Turkish individuals that yields a difference of more than 12 years.
AB - Dental features can be considered as the best candidate feature for post-mortem identification. If ante-mortem data is unavailable, then forensic experts are needed for reducing the search space by creating post-mortem dental profiling. Age is one of important factors in dental profiling. Manual inspection of dental radiographs suffers from two drawbaks, i.e., intraobserver error and interobserver error. This paper proposed a semi-automatic system for age estimation. There are two phases in developing the proposed system, i.e., the modeling phase and the estimation phase. The modeling phase is the stage for deriving an estimation formula based on known data. In this paper, we use data taken from Javanese people. The estimation phase include the process of defining a Region of Interest (ROI), automatic length computation, and age estimation based on the derived modeling formula. Our experiments showed a promising result, i.e., an average absolute error of 5.2 years, compared to application of the Kvaal method to panoramic radiographs from Turkish individuals that yields a difference of more than 12 years.
KW - Age estimation
KW - Human identification
KW - Image processing
KW - Panoramic radiographs
KW - Regression
UR - http://www.scopus.com/inward/record.url?scp=84888865319&partnerID=8YFLogxK
U2 - 10.12928/telkomnika.v11i1.905
DO - 10.12928/telkomnika.v11i1.905
M3 - Article
AN - SCOPUS:84888865319
SN - 1693-6930
VL - 11
SP - 199
EP - 206
JO - Telkomnika (Telecommunication Computing Electronics and Control)
JF - Telkomnika (Telecommunication Computing Electronics and Control)
IS - 1
ER -