Project Title: Gabor Filter for Fingerprint Recognition

Brief Introduction:

Fingerprint recognition is one of the most practices and this can be popular for recognition with greater degree of success. The fingerprint has characteristics that are unique minutiae, that are points where a curve track finishes, intersect or branches down. A novel technique for Fingerprint recognition is known as in this work employing a mixture of Fast Fourier Transform (FFT) and Gabor Filters to improvement the image. The proposed strategy involves mix of Gabor filter and Frequency domain filtering for improving the fingerprint. With eight various orientations of Gabor filter, top options that come with the fingerprint are extracting and are also additionally combined. The fingerprint image is subdivided into 32*32 structures that are little Frequency domain filtering. Features are removed from most of these structures in regularity domain. Final fingerprint that is enhanced obtained the full total outcomes of Gabor Filter and frequency domain filtering. Binarization and Thinning follows next where the fingerprint that is improved turned into binary therefore the ridges are thinned to one or more pixel width. This can help in extracting the Minutiae elements. Euclidian distance method ideal for performance of recognition. The general recognition rate for the proposed technique is 95% acquired as which is far better in comparison to histogram strategy where the recognition price is 64%.

Hardware Details:

* Gabor Filter

* fingerprint verification combination 2002(FVC 2002).

Software Details:

• MATLAB

Block Diagram:

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