Hardware design for binarization and thinning of fingerprint images

TL;DR

This paper presents a hardware pipeline architecture for real-time fingerprint image binarization and thinning, introducing adaptive thresholding, optimal block size selection, and dilation to improve minutiae detection accuracy.

Contribution

It proposes a novel hardware pipeline for fingerprint image binarization and thinning, including adaptive thresholding and optimized block size selection.

Findings

Achieved real-time processing capability.

Reduced false minutiae detection through dilation.

Developed an efficient pipeline for thinning algorithm implementation.

Abstract

Two critical steps in fingerprint recognition are binarization and thinning of the image. The need for real time processing motivates us to select local adaptive thresholding approach for the binarization step. We introduce a new hardware for this purpose based on pipeline architecture. We propose a formula for selecting an optimal block size for the thresholding purpose. To decrease minutiae false detection, the binarized image is dilated. We also present in this paper a new pipeline structure for implementing the thinning algorithm