A comparative study of fuzzy evolutionary techniques for footprint recognition and performance improvement using wavelet-based fuzzy neural network Online publication date: Sun, 25-Aug-2013
by V. Devadoss Ambeth Kumar; M. Ramakrishnan
International Journal of Computer Applications in Technology (IJCAT), Vol. 48, No. 2, 2013
Abstract: Wavelet and fuzzy neural network is the technique used in the implementation of footprint recognition system. The transformation of the footprint image is done by the wavelet to detect the edge and then according to the statistical distribution disciplinarians of different toe images the membership functions are constructed, keeping the angle and length as parameters. These obtained values are used as single judgement factor. The input to the neural network is given by computing the distance vector between the four model vectors and the comprehensive judgement vector. Template matching is based on the resultant percentage, if it is above 70 then it returns the output as matched else it returns the output as invalid or no match found. Since this wavelet-based method is based on fuzzy neural network, it reflects the different shapes of toe image subjectively and correctively, the test results show noteworthy improvements in recognition rate.
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Computer Applications in Technology (IJCAT):
Login with your Inderscience username and password:
Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.
If you still need assistance, please email subs@inderscience.com
Our Blog 
Follow us on Twitter 
Visit us on Facebook