Signature Matching Using Associative Memory with Reusing of Pruned Nodes
|International Journal of Engineering Trends and Technology (IJETT)||
|© 2017 by IJETT Journal|
|Year of Publication : 2017|
|Authors : K. Nagi Reddy, Dr.B Ravi Prasad, Dr.K.Suvarchala
|DOI : 10.14445/22315381/IJETT-V43P203|
K. Nagi Reddy, Dr.B Ravi Prasad, Dr.K.Suvarchala "Signature Matching Using Associative Memory with Reusing of Pruned Nodes", International Journal of Engineering Trends and Technology (IJETT), V43(1),10-16 January 2017. ISSN:2231-5381. www.ijettjournal.org. published by seventh sense research group
Signature matching has been a topic of interest for quite some time. The need for efficient and robust algorithms and systems for recognition is being experienced in India especially in the post and telegraph department, banking sector and police department. In this paper signature image database retrieval has been investigated with special consideration. In unformatted databases one of the important features is that the user tends to retrieve information based on approximate queries, which are quite common in practice and sometimes unintentional. Work has been done on signature matching earlier using conventional and hybrid methods which may not be very efficient for practical systems. The present work is a new direction in signature matching using artificial neural networks and an implementation of a comprehensive software, based on signature matching in practice. Our procedure involves capturing the signature image, preprocessing, indexing each signature image through wavelets, thresholding and retrieving the stored signature for the given query signature pattern using associative memory concept of Dynamical Neural Network (DNN) with reuse. It is proved that the performance of the dynamical neural network with reuse using the learning strategy for signature matching is very efficient.
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—associative memory, dynamical neural network, spurious states, string descriptor, thresholding, POSC