Paper Title
Fourier Transform Based Fingerprint Image Processing for Accurate Minutiae Detection and Fast Computation

Abstract
This paper presents a comprehensive review of fingerprint image enhancement by applying a multi-stage processing pipeline, with the focus being on the detection of key minutiae features, namely bifurcation and termination points. Contrast Limited Adaptive Histogram Equalization, normalization, Fourier enhancement, binarization, thinning, and gradient filtering make up the pipeline. The influence of each stage on the number of minutiae detected is assessed with reference to a set of fingerprint images. Results show that although the different stages of processing in general, particularly CLAHE and Fourier enhancement, considerably improve the contrast and clarity, they also add subtle variations into minutiae detection, most of which are related to noise reduction or ridge structure enhancement. On the whole, final processed images balance enhanced details with minimal noise, which explains why the counts of minutiae remain very close to those detected in the original images. This consistency is important for the preservation of accuracy and reliability in the fingerprint recognition system. Results underline the role each stage can play during the enhancement process to refine features of fingerprints, which will be helpful in developing robust biometric identification technologies. Keywords - Image, Fingerprints, Pixel, Gabor filter, Fourier Transform