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

A New Dynamic Feature Extraction Method for Biometric Images

Emre AVUÇLU
Abdullah ELEN
Ayhan ÖZÇİFÇİ
Pages
983–988
DOI
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

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

📌 3 Key Takeaways

🎯
Objective & Hypothesis:The image of biometric properties in humans is used in many fields today.
📊
Key Findings & Data:In this study, automatic and dynamic image segmentation was performed by using 300x300 fingerprint images.
💡
Conclusion & Impact:The developed segmentation and feature extraction algorithm can be applied to any image of equal size.
🔬Design:Research Article
📍Scope:Comprehensive Sample
⚙️Variables:Image segmentation · feature extraction · fingerprint images

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.

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.

🔖

Cite This Article

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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