Clustering Pola Sidik Jan Menggunakan Jaringan Syaraf Tiruan Kohonen Self Organizing Maps  

Oleh:

Mohammad, Isa Irawan

Jenis: Article from Journal - ilmiah nasional - tidak terakreditasi DIKTI
Dalam koleksi: Gematika: Jurnal Manajemen Informatika vol. 5 no. 2 (Jun. 2004), page 96-101.
Topik: saraf tiruan; clustering phole; image processing; artificial neural network; kohonen - self organizing maps (SOM)

Ketersediaan

Perpustakaan Pusat (Semanggi) Nomor Panggil: GG4.1 Non-tandon: 1 (dapat dipinjam: 0) Tandon: tidak ada

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Isi artikel

One way, that can be used to identify persons, is on their fingerprint or it can be known as identification biometric system. In this research Kohonen Self Organizing Maps Artificial Neural Network is used in clustering fingerprint image. Network is tested in clustering neighbourhood weight R between 1 till 10 and learning rate a = 0.9. The network can be classified fingerprint image based on the general characteristic that is implemented into Kohonen Artificial Neural Network model to identifiy five class of eight class available, they are : Radial Loop, Ulnar Loop, Accidental Whorl, Plain Whorl, and Tented Arch.

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