Offline Handwritten Signature Recognition Based on Upper and Lower Envelope Using Eigen Values

Jagtap, Amruta B.; Hegadi, Ravindra S.

doi:10.1109/wccct.2016.62

Cited by 12 publications

(1 citation statement)

References 2 publications

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“…Hybrid Local and global features are used for identify the genuine signature form forded signature [12,13]. Eigen value technique applied for signature verification system [14]. Siamese Neural Network (SNN) used for classification of genuine and forged signatures [15].…”

Section: Literature Reviewmentioning

confidence: 99%

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

Kiran¹,

Parameshachari

Yashwanth³

et al. 2021

SN COMPUT. SCI.

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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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Section: Literature Reviewmentioning

confidence: 99%