CLASSIFYING FINGERPRINT IMAGES ACCORDING TO FINGERPRINT PATTERNS USING CANNY EDGE DETECTION & EUCLIDEAN DISTANCE METHOD

DINATA, IE MARCO (2021) CLASSIFYING FINGERPRINT IMAGES ACCORDING TO FINGERPRINT PATTERNS USING CANNY EDGE DETECTION & EUCLIDEAN DISTANCE METHOD. Other thesis, Universitas Katholik Soegijapranata Semarang.

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Abstract

Every single person in this earth has a unique fingerprint pattern hence everyone will have different fingerprint pattern. Those differences resulting in very many types of fingerprints. So, this research was conducted to groups those many types of fingerprints based on their patterns. This project was conducted thorough several process. First, the system went through an image acquisition or image taking process. The image will be taken by using a scanner and also camera with JPG format. Then the image will enter the cropping steps, in which this steps was done with aim to get an image of the fingerprint only. Afterwards, the image will be converted to grayscale image with meaning that those image will only have 1 value in every pixels so it will ease the next process. After that, the image will then be resized to synchronize the size of the image so it will be easier to be processed. Then, after passing every single steps of preprocessing, the image will enter the extraction steps where canny edge detection method was used. Lastly, the image will enter the calculation in which the Euclidean distance will be calculated. The result from this project were that the fingerprint will be able to be grouped into several groupings based on the patterns and able to obtain the accurate results from 2 ways, which were through scanner and stamp.

Item Type:	Thesis (Other)
Subjects:	000 Computer Science, Information and General Works > 005 Computer programming, programs & data
Divisions:	Faculty of Computer Science > Department of Informatics Engineering
Depositing User:	mr AM. Pudja Adjie Sudoso
Date Deposited:	23 Jun 2021 03:52
Last Modified:	23 Jun 2021 03:52
URI:	http://repository.unika.ac.id/id/eprint/25847

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