Pengenalan tanda tangan melalui pengolahan citra digital dan jaringan saraf tiruan radial basis function

Ricardo, Ignatius (2012) Pengenalan tanda tangan melalui pengolahan citra digital dan jaringan saraf tiruan radial basis function. Bachelor thesis, Universitas Pelita Harapan.

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Abstract

Tanda tangan adalah salah satu keunikan yang dimiliki oleh setiap orang sehingga seringkali dipakai dalam menentukan keabsahan dari suatu dokumen atau transaksi. Sistem yang dibuat bertujuan untuk melakukan pengenalan tanda tangan secara efisien serta mengetahui manfaat pengolahan citra digital dan jaringan saraf tiruan Radial Basis Function dalam dunia nyata. Sistem ini dibuat dengan menerapkan pengolahan citra digital dan pemanfaatan jaringan saraf tiruan Radial Basis Function. Citra tanda tangan yang akan dilatih atau diuji harus melalui beberapa proses pengolahan citra digital yaitu proses pengubahan citra menjadi citra keabuan (grayscale), pengambangan (thresholding), segmentasi citra (segmentation), normalisasi ukuran citra (size normalization), thinning, dan pembagian citra ke dalam wilayah-wilayah (region) yang akan menghasilkan nilai-nilai untuk selanjutnya diproses dengan jaringan saraf tiruan Radial Basis Function. Pemanfaatan jaringan saraf tiruan Radial Basis Function dimulai dengan pelatihan terhadap sampel tanda tangan dari setiap responden yang telah diolah. Setelah proses pelatihan selesai maka sebuah citra tanda tangan milik salah satu responden yang telah dilatih dapat dikenali oleh sistem. Pengolahan citra tanda tangan dan jaringan saraf tiruan Radial Basis Function yang diterapkan dalam sistem berhasil melakukan pengenalan terhadap beberapa citra tanda tangan. Penelitian ini menguji 100 citra tanda tangan yang berasal dari 10 responden yang telah masing-masing telah memberikan lima citra tanda tangan untuk pelatihan sistem. Tingkat akurasi dari hasil pengujian tersebut sebesar 88% dimana terdapat 88 tanda tangan yang dapat dikenali dengan benar dan 12 tanda tangan yang gagal dikenali. / Signature is one of the each individual’s uniqueness; therefore this is often used to determine the authenticity of a document or transaction. The system is being created to efficiently recognize a signature, this also determine the function of digital image processing and Radial Basis Function neural network as implemented in the actual basis. This system is made by implementing digital image processing and the usage of Radial Basis Function neural network. Signature image that will be exercised or tested has to follow few digital image processes namely grayscale, threshold, segmentation, size normalization, thinning, and region to produce values which subsequently will be processed using Radial Basis Function neural network. The usage of Radial Basis Function neural network is started by conducting exercise toward processed signature sample from each respondent. After exercise process is finished, then a signature image owned by a respondent who has been exercised can be recognized by the system. The signature image process and Radial Basis Function neural network which has been implemented in the system successfully recognizes few signature image. This research tests 100 signature images which comes from 10 respondents which individually has provided five signatures to system exercise. The accuracy degree from testing result is 88% where there are 88 signatures that can be correctly recognized while the 12 signatures are failed to be identified.

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