Klasifikasi Stempel Dokumen Berwarna Menggunakan Fuzzy Integral dan Artificial Neural Networks

https://doi.org/10.5614/joki.2011.3.1.3

Authors

  • A Budiman
  • B. H. Iswanto

Abstract

Abstrak

Berkembangnya teknologi pencetakan meningkatkan rawannya tindakan pemalsuan, maka dibutuhkan sistem identifikasi dan klasifikasi yang bersifat non-destruktif  yang dapat diterapkan di dokumen. Stempel pada dokumen berwarna dapat dijadikan objek penciri keaslian suatu dokumen. Integral fuzzy Sugeno dan Choquet dipilih sebagai operator terbobot fusi data sinyal multi-kanal untuk ekstraksi stempel sebagai objek penciri. Metode ini dapat memberikan variasi maksimum pada citra keabuan terhadap cluster stempel warna yang ada pada citra dokumen. Hasil extraksi ciri diukur tingkat eccentricity, yang menunjukkan hasil extraksi ciri stempel masih berbentuk melingkar (roundnes). Tingkat pengenalan data uji menggunakan ANN bernilai 100% dari keseluruhan citra uji, yang berarti artificial neural networks  dapat mengenali semua stempel uji. Pada tahap pengujian keaslian dokumen, menguji stempel hasil cetak printer menghasilkan tingkat pengenalan keaslian sebesar 80,1%.

Kata kunci: integral fuzzy, artificial neural networks, pengolahan citra.


Abstract

The development of printing technology, increase the susceptibility of counterfeiting measures, the identification and classification system is needed that is non-destructive that can be applied in the document. Stamp color at documents can be made as the object featureof the authenticity of a document. Sugeno and Choquet fuzzy integral is selected as the operator weighted data fusion of multi-channel signal for the extraction of stamps as objects feature. This method can give a maximum variation in the gray image of the cluster color stamp on the document image. The result of feature extraction measured levels of eccentricity, which shows the results of feature extraction is still a circular stamp (roundness). Recognition level test data using ANN worth 100% of the overall image of the test, which means the artificial neural networks identify all test seals. At the authenticity of documents testing that examine stamp that prints by printer, resulting in recognition rate of 80.1% authenticity.

Keywords: fuzzy Integral, artificial neural network, image processing.

Published

2011-04-15

How to Cite

[1]
A. Budiman and B. H. Iswanto, “Klasifikasi Stempel Dokumen Berwarna Menggunakan Fuzzy Integral dan Artificial Neural Networks”, JOKI, vol. 3, no. 1, p. 87, Apr. 2011.

Issue

Vol. 3 No. 1 (2011): Jurnal Otomasi, Kontrol, dan Instrumentasi

Section

Articles
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