Binary Fingerprint Image Thinning Using Template-Based PCNNs

Authors:
Luping Ji;Zhang Yi;Lifeng Shang;Xiaorong Pu
Affiliations:
Univ. of Electron. Sci. & Technol. of China, Chengdu;-;-;-
Venue:
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Year:
2007

Citing 0
Cited 6

Fingerprint orientation field estimation using ridge projection

Pattern Recognition
Fingerprint orientation field estimation using ridge projection

Pattern Recognition
Extraction of Line Feature in Binary Images

IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences
Review article: Review of pulse-coupled neural networks

Image and Vision Computing
A neuron-MOS-based VLSI implementation of pulse-coupled neural networks for image feature generation

IEEE Transactions on Circuits and Systems Part I: Regular Papers
A novel neural network method for shortest path tree computation

Applied Soft Computing

Quantified Score

Hi-index	0.00

Visualization

Abstract

This correspondence presents a coarse-to-fine binary-image-thinning algorithm by proposing a template-based pulse-coupled neural-network model. Under the control of coupled templates, this algorithm iteratively skeletonizes a binary image by changing the load signals of pulse neurons. A direction-constraining scheme for avoiding fingerprint ridge spikes has been discussed. Experiments show that this algorithm is effective for fingerprint thinning, as well as other common images. Moreover, this algorithm can be coupled with a fingerprint identification system to improve the recognition performance.