Designing and Making Designing and Making Application To Recognize Application To Recognize

Signatures Using Signatures Using BackpropagationBackpropagation

Ronny Harianto26406037

BackgroundBackgroundSignatures 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.

TheoryTheoryThresholding

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.

TheoryTheoryWidth 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

TheoryTheoryBackpropagation

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 ApplicationDesign System And Application

Process Image FormProcess Image Form

Training FormTraining FormLearning Rate

Jumlah hidden layer

Jumlah hidden node tiap layer

Training Now

Epoch

SSE

Recognize FormRecognize Form

Original Image Process è Result Image

RecognizeBrowse

Result for signatures drilledResult for signatures drilledWith 10 hidden layer on first layer (90%)

Nama Jumlah sampel yang dikenali Jumlah sampel yang tidak dikenali

Persentase Keberhasilan

David 45 5 90%

Ivan 47 3 94%

Merlina 45 5 90%

Nyoto 38 12 76%

Riky 44 6 88%

Ronny 46 4 92%

Yohanes 50 0 100%

Result for signatures drilledResult for signatures drilledWith 20 hidden layer on first layer (94.8571%)

Nama Jumlah sampel yang dikenali Jumlah sampel yang tidak dikenali

Persentase Keberhasilan

David 47 3 94%

Ivan 50 0 100%

Merlina 49 1 98%

Nyoto 45 5 90%

Riky 45 5 90%

Ronny 46 4 92%

Yohanes 50 0 100%

Result for signatures wasn’t drilledResult for signatures wasn’t drilledWith 10 hidden layer on first layer (94.2857%)

Nama Jumlah sampel yang dikenali Jumlah sampel yang tidak dikenali

Persentase Keberhasilan

David 5 0 100%

Ivan 5 0 100%

Merlina 5 0 100%

Nyoto 4 1 80%

Riky 5 0 100%

Ronny 4 1 80%

Yohanes 5 0 100%

Result for signatures wasn’t drilledResult for signatures wasn’t drilledWith 20 hidden layer on first layer (94.2857%)

Nama Jumlah sampel yang dikenali Jumlah sampel yang tidak dikenali Persentase Keberhasilan

David 5 0 100%

Ivan 5 0 100%

Merlina 5 0 100%

Nyoto 4 1 80%

Riky 5 0 100%

Ronny 4 1 80%

Yohanes 5 0 100%