In the usage of the biometrics for the authentication finger print is most commonly used biometric. The process of extraction of the feature points from images were based on point extraction methods or texture pattern identification. Miniatures and Bifurcations were the feature points commonly extracted from the image. The input finger print images were enhanced based on wavelet based enhancement process. Discrete Wavelet Transformation is employed for the enhancement process. From the enhanced images the miniature features were extracted from the input images. The input finger print images were obtained from the dataset. The finger print images were first filtered using Bilateral filtering process. In bilateral filter the intensity value at each pixel in an image is replaced by a weighted average of intensity values from nearby pixels. This weight can be based on a Gaussian distribution. As a result of the bilateral filter the input finger images were smoothened. The filtered image is then enhanced based on Wavelet based enhancement and Gabor filter process. The wavelet based enhancement process decompose the input image based on Discrete Wavelet Transformation process. The decomposed coefficients were then enhanced based on Coefficient enhancement process. A filter bank consisting of Gabor filters with various scales and rotations is created. The filters are convolved with the signal resulting in the enhanced image. The input finger print images were obtained from the dataset. The finger print images were first filtered using Bilateral filtering process. In bilateral filter the intensity value at each pixel in an image is replaced by a weighted average of intensity values from nearby pixels. This weight can be based on a Gaussian distribution. As a result of the bilateral filter the input finger images were smoothened. The filtered image is then enhanced based on Gabor filter process. A filter bank consisting of Gabor filters with various scales and rotations is created. The filters are convolved with the signal resulting in the enhanced image. With the help of Gabor filter the ridges in the finger print regions can be identified. The identified ridge regions were enhanced based on the comparison of the detected regions with the original image. The Gaussian filter enhances the input image resulting in the finger print image with enhanced ridges. The ridges and bifurcation points were extracted from the image. The ridge regions were identified by identifying the parallel finger print regions in the images. The bifurcation regions were identified by identifying crossing finger print regions in the images.