Identification Of Signature Using Zoning Methods And Support Vector Machine
Identification of signatures is the process of identifying and defining a person's signature. Identification of signatures including biometics that use natural human behavior. Identification of signatures can be used in security areas such as money withdrawal permits, check validation, credit card transactions and more. During this signature identification is done manually. Difficulty in this way, if the signature to be identified is large, the examiner will experience fatigue. To simplify it needs to be developed to create a computerized signature identification system. In this research, the development of this signature identification is done using the method of zoning and Support Vector Machine (SVM) classification. Based on the tests that have been done, normal test data test resulted in recognition accuracy of 95.31%. In testing the test data with disturbance obtained accuracy of 20.31%. While the testing of artificial signatures generated an accuracy of 70%. In addition to the registered signature image pattern, there are also signature images that are not registered in the database. The accuracy obtained in this test is 100%..
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