# Designing and Making Application To Recognize Signatures Using Backpropagation Ronny Harianto 26406037.

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Designing and Making Application To Recognize Signatures Using Backpropagation Ronny Harianto 26406037

Background Signatures can be interpreted as one form of identification. Every people have different signatures, because their intensity level, writing style, and proportion. Because they have unique signatures, then I make an application to recognize the signatures.

Theory Thresholding  Thresholding is a process to change the value pixel of the image to 0 and 255(bi-level image). Noise Reduction  Noise Reduction is use to clean the image from noise which has form of point. Segmentation  Segmentation is use to retrieve the required object from the image.

Theory Width Normalization  Width nomalization is use to uniform the size of image. Thinning  Thinning is used to retrieve a structure from image. Region  Region is used to convert an image to a value that can be read by backpropagation  Image is divide into 12 regions

Theory Backpropagation  Backpropagation is the one of the learning algorithm in artificial neural network.  Learning process is done by adjusting the weight of the artificial neural networks with backward direction based on the error value in the learning process.

Design System And Application

Process Image Form

Training Form

Recognize Form

Result for signatures drilled With 10 hidden layer on first layer (90%) NamaJumlah sampel yang dikenali Jumlah sampel yang tidak dikenali Persentase Keberhasilan David45590% Ivan47394% Merlina45590% Nyoto381276% Riky44688% Ronny46492% Yohanes500100%

Result for signatures drilled With 20 hidden layer on first layer ( 94.8571%) NamaJumlah sampel yang dikenali Jumlah sampel yang tidak dikenali Persentase Keberhasilan David47394% Ivan500100% Merlina49198% Nyoto45590% Riky45590% Ronny46492% Yohanes500100%

Result for signatures wasn’t drilled With 10 hidden layer on first layer (94.2857%) NamaJumlah sampel yang dikenali Jumlah sampel yang tidak dikenali Persentase Keberhasilan David50100% Ivan50100% Merlina50100% Nyoto4180% Riky50100% Ronny4180% Yohanes50100%

Result for signatures wasn’t drilled With 20 hidden layer on first layer ( 94.2857%) NamaJumlah sampel yang dikenali Jumlah sampel yang tidak dikenali Persentase Keberhasilan David50100% Ivan50100% Merlina50100% Nyoto4180% Riky50100% Ronny4180% Yohanes50100%

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