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Ryan Bagus Wicaksono
Telkom University
Computer Science & IT Electrical & Electronics Engineering

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Human height and weight classification based on footprint using gabor wavelet and K-NN methods Ryan Bagus Wicaksono; Suci Aulia; Sugondo Hadiyoso; Bambang Hidayat
JURNAL INFOTEL Vol 14 No 2 (2022): May 2022
Publisher : LPPM INSTITUT TEKNOLOGI TELKOM PURWOKERTO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20895/infotel.v14i2.728

Abstract

Height and weight are parameters to identify a person, especially for a forensic. To identify height and weight is usually done manually. In addition to manually using height measuring devices and scales, you can also use information related to the foot length. There is a relationship between height and foot length can be expressed in the correlation coefficient (r) as same as for weight. Therefore, in this study, a system for measuring human height and weight based on images of the footprint is implemented on Android. The methods used in this study are Gabor Wavelet and k-Nearest Neighbor (k-NN). The simulation results generate the best accuracy of 75%. The system can also used to categorize the ideal body level according to the Body Mass Index (BMI). The system is able to process images with an average computation time of 8.92 seconds.
Co-Authors Bambang Hidayat Suci Aulia Sugondo Hadiyoso