Abstract
Biometric recognition of infant identification systems is critical in security access for identification and verification systems. However, until now, hospitals or health centres in Indonesia still use conventional biometric identification, such as stamping or inking on the soles of babies' feet affixed to paper and are very vulnerable to the risk of damage or loss of data. To resolve this problem, computer vision technology can accurately identify the baby's feet' soles with the final result in the form of digital data. This study compares the classification method of baby feet using the SVM (Support Vector Machine) algorithm with the K-Nearest Neighbor algorithm. The baby's feet understudy image was taken using a cellphone camera with sample data of 3 months old babies. Comparing the SVM and KNN classification methods obtained high accuracy, precision and recall values, namely 98.80% accuracy, 89.51% precision and 88.00% recall. (for the SVM Gaussian kernel classification), with an accuracy of 99.08%, 92.65% precision and 90.75% recall (for the KNN Ecluidean Distance classification), it can be concluded that the KNN classification method using Euclidean distance is the best for applied in the baby palm identification system using the geometric image feature.
Highlights
The case of the loss or exchange of a newborn baby is a disaster that parents greatly fear around the world
The biometric method in newborns that is easiest to obtain is on the soles of the baby's feet, and this is proven because until now the baby's footprint method is still used as a marker for newborns, research on the biometric identification system for newborns uses the geometric method
True positives (TP) is the number of positive data records classified as positive values, false positives (FP) is the number of negative data records classified as positive values, false negatives (FN) is the number of positive data records classified as positive values, true negatives (TN) is the number of negative data records classified as negative values
Summary
The case of the loss or exchange of a newborn baby is a disaster that parents greatly fear around the world. Issues of loss or exchange of newborns often occur because the newborn recognition system used until now still uses ink-stamp media for baby feet and name bracelets on paper which are usually damaged or lost [1]. The development of increasingly sophisticated computer vision technology can replace conventional self-recognition systems with the Biometric identification method. The biometric methods that are usually used as self-recognition systems are the fingerprint system, iris, facial recognition system, voice, geometry, and texture or fingerprints. The soles of baby's feet, which are expected to replace conventional recognition systems applied by hospitals, switch to a more modern system with the support of Computer Vision technology
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