Title: A comparative study of fuzzy evolutionary techniques for footprint recognition and performance improvement using wavelet-based fuzzy neural network
Authors: V. Devadoss Ambeth Kumar; M. Ramakrishnan
Addresses: Department of Computer Science and Engineering, Sathyabama University, Chennai, 600119, India ' Information Technology, Velammal Engineering College, Chennai, 600066, India
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.
Keywords: footprint recognition; performance improvement; wavelets; region of interest; ROI; fuzzy neural networks; FNN; footprint images; edge detection; toe images.
International Journal of Computer Applications in Technology, 2013 Vol.48 No.2, pp.95 - 105
Received: 08 May 2021
Accepted: 12 May 2021
Published online: 24 Aug 2013 *