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Offline Signature Recognition Using Image Processing Techniques and Back Propagation Neuron Network System


As the technology improves, there are many new innovations which give the security frameworks with different methods that are used to identify a person. Signature recognition is one of methods used to identify person. In this paper, offline signature recognition using back propagation neuron network system and image processing techniques has been proposed. Preprocessing of signature can be done using image processing techniques which involves RGB2Gray conversion, filtering, adjusting, thresholding followed by canny edge detection and at the last image scaling applied to reduce the processing time. Processed image feature is extracted using back propagation neuron network system with defined number of neurons and hidden layers. Similarly, data set images undergo preprocessing operation and features are extracted. Based on number of layers that are hidden and neuron, better recognition rate is obtained. The proposed method shows that the experimental result has more success rate.

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Correspondence to P. Kiran.

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This article is part of the topical collection “Data Science and Communication” guest edited by Kamesh Namudri, Naveen Chilamkurti, Sushma S J and S. Padmashree.

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Kiran, P., Parameshachari, B.D., Yashwanth, J. et al. Offline Signature Recognition Using Image Processing Techniques and Back Propagation Neuron Network System. SN COMPUT. SCI. 2, 196 (2021).

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