Articles
33
Documents
Reconstruction of Planar Multilayered Structures using Multiplicative-Regularized Contrast Source Inversion

TELKOMNIKA Telecommunication, Computing, Electronics and Control Vol 11, No 3: September 2013
Publisher : Universitas Ahmad Dahlan

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Abstract

There is an increasing interest to have an access to hidden objects without making any destructive action. Such non-destructive method is able to give a picture of the inner part of the structure by measuring some external entities. The problem of reconstructing planar multilayered structures based on given scattering data is an inverse problem. Inverse problems are ill-posed, beside matrix inversion tools, a regularization procedure must be applied additionally. Multiplicative regularization was considered as an appropriate penalty method to solve this problem. The Gauss-Newton inversion method as an optimization procedure was used to find the permittivity values, which minimized some cost functions. Several dielectric layers with different thickness and profiles were observed.Some layers needed more discretization elements and more iteration steps to give the correct profiles.

Hierarchical Gaussian Scale-Space on Androgenic Hair Pattern Recognition

TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 15, No 1: March 2017
Publisher : Universitas Ahmad Dahlan

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Abstract

Androgenic hair pattern stated to be the new biometric trait since 2014. The research to improve the performance of androgenic hair pattern recognition system has begun to be developed due to the problems that occurred when other apparent biometric trait such as face is hidden from sight. The recognition system was built with hierarchical Gaussian scale-space using 4 octaves and 3 levels in each octave. The system also implemented the equalization process to adjust image’s intensity by using histogram equalization. We analyzed 400 images of androgenic hair in the database that were analyzed using 2-fold and 10-fold cross validation and Euclidean distance to classify it. The experimental results showed that our proposed method gave better performance compared to previous work that used Haar wavelet transformation and principal component analysis as the main method. The best recognition precision was 94.23 % obtained from the base octave with the third level using histogram equalization and 10-fold cross validation.