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Dergiler / Politeknik Dergisi / 2021 / Cilt: 24 - Sayı: 3

A New Dynamic Feature Extraction Method for Biometric Images

Emre AVUÇLU
Abdullah ELEN
Ayhan ÖZÇİFÇİ
Sayfa
983–988
DOI
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Yapay Zeka Hızlı Bakış & Çıkarımlar

AI Insight
⚡ TL;DR(1 Cümlede Hızlı Çıkarım)

The developed segmentation and feature extraction algorithm can be applied to any image of equal size.

📌 3 Maddede Bu Makale

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Amaç & Hipotez:The image of biometric properties in humans is used in many fields today.
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Temel Bulgular & Veri:In this study, automatic and dynamic image segmentation was performed by using 300x300 fingerprint images.
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Sonuç & Katkı:The developed segmentation and feature extraction algorithm can be applied to any image of equal size.
🔬Tür:Araştırma Makalesi
📍Kapsam:Genişletilmiş Akademik Örneklem
⚙️Değişkenler:Image segmentation · feature extraction · fingerprint images

Özet

The image of biometric properties in humans is used in many fields today. Regardless of these features, it is necessary to first translate it into data that the computer understands. In this study, automatic and dynamic image segmentation was performed by using 300x300 fingerprint images. A fingerprint database with a total of 80 images and 10 different classes was used. The features of the images were subtracted from the sub-segments obtained from these images by the feature extraction algorithm that was originally developed. The 300x300 images were divided into 25x25 sub-images and the feature vector was obtained. 144x80 inputs obtained after image segmentation were kept in areas in separate tables. The developed segmentation and feature extraction algorithm can be applied to any image of equal size.

Abstract

The image of biometric properties in humans is used in many fields today. Regardless of these features, it is necessary to first translate it into data that the computer understands. In this study, automatic and dynamic image segmentation was performed by using 300x300 fingerprint images. A fingerprint database with a total of 80 images and 10 different classes was used. The features of the images were subtracted from the sub-segments obtained from these images by the feature extraction algorithm that was originally developed. The 300x300 images were divided into 25x25 sub-images and the feature vector was obtained. 144x80 inputs obtained after image segmentation were kept in areas in separate tables. The developed segmentation and feature extraction algorithm can be applied to any image of equal size.

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Bu Makaleye Atıf Yap

AVUÇLU, E., ELEN, A., ÖZÇİFÇİ, A. (2021). A New Dynamic Feature Extraction Method for Biometric Images. Politeknik Dergisi, Cilt: 24 - Sayı: 3, 983–988. https://ajindex.com/articles/340504

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Kaynakça (15)

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