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Skull Sex Estimation Based on Wavelet Transform and Fourier Transform.

Wen Yang¹, Mingquan Zhou^1,2, Pengfei Zhang¹

¹College of Information Science and Technology, Northwest University, Xi'an, China.

Biomed Research International

|May 19, 2020

Summary

This study developed an objective skull sex estimation model for the Chinese population using wavelet and Fourier transforms. The new method achieves high accuracy, outperforming traditional techniques in forensic anthropology.

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Area of Science:

Forensic Anthropology
Biometrics
Medical Imaging Analysis

Background:

Skull sex estimation is vital in forensic investigations for identifying individuals.
Traditional methods rely on subjective morphological and measurement techniques.
There is a need for objective and accurate sex estimation models.

Purpose of the Study:

To develop an objective skull-based sex estimation model for the Chinese population.
To provide a scientific reference for forensic medicine and anthropology.
To evaluate the efficacy of wavelet and Fourier transforms combined with SVM for sex estimation.

Main Methods:

Utilized wavelet transform and Fourier transform to quantify features of the superior orbital margin and frontal bone.
Employed Support Vector Machine (SVM) for classification of extracted features.
Tested the developed model on a Chinese population dataset.

Main Results:

Achieved high accuracy rates for sex discrimination: 90.9% for males and 94.4% for females.
Demonstrated superior performance compared to traditional morphological and measurement methods.
The proposed method offers greater objectivity and a stronger theoretical basis.

Conclusions:

The developed objective sex estimation model using wavelet and Fourier transforms is effective and accurate for the Chinese population.
This technique provides a more objective and reliable alternative to traditional methods in forensic anthropology.
The findings support the practical application of advanced signal processing and machine learning in forensic identification.