# A Fingerprint-Based Verification Framework Using Harris and SURF Feature Detection Algorithms
###### Abstract  
Amongst all biometric-based personal authentication systems, a fingerprint that gives each person a unique identity is the most commonly used parameter for personal identification. In this paper, we present an automatic fingerprint-based authentication framework by means of fingerprint enhancement, feature extraction, and matching techniques. Initially, a variant of adaptive histogram equalization called CLAHE (contrast limited adaptive histogram equalization) along with a combination of FFT (fast Fourier transform), and Gabor filters are applied to enhance the contrast of fingerprint images. The fingerprint is then authenticated by picking a small amount of information from some local interest points called minutiae point features. These features are extracted from the thinned binary fingerprint image with a hybrid combination of Harris and SURF feature detectors to render significantly improved detection results. For fingerprint matching, the Euclidean distance between the corresponding Harris-SURF feature vectors of two feature points is used as a feature matching similarity measure of two fingerprint images. Moreover, an iterative algorithm called RANSAC (RANdom SAmple Consensus) is applied for fine matching and to automatically eliminate false matches and incorrect match points. Quantitative experimental results achieved on FVC2002 DB1 and FVC2000 DB1 public domain fingerprint databases demonstrate the good performance and feasibility of the proposed framework in terms of achieving average recognition rates of 95% and 92.5% for FVC2002 DB1 and FVC2000 DB1 databases, respectively. f 2021  
fingerprint according to the number ID and matches the fingerprint obtained in real-time from the user with the template. Fingerprint identification is to define the person's identity via fingerprint(s). Without knowing the person's identity, the fingerprint identification system attempts to match his fingerprint with those in the entire fingerprint database [3], as depicted in the block diagram shown in Figure 1.  
Furthermore, the purpose of fingerprint matching is to find out if two sets of fingerprints are similar or not; one fingerprint is stored in the database and the other is the current fingerprint [4]. Fingerprint matching approaches can be roughly categorized into three families:  
* _Correlation-based matching_: In this approach, two fingerprints are placed on top of each other and the correlation among the corresponding pixels is matched for various alignments (different displacement and rotations). The principal disadvantage of correlation-based matching is its computational complexity. Moreover, it requires an accurate position of the recording point and is affected by non-linear distortion. * _Minutiae-based matching_: This approach is the most common and used method, where the fundamental fingerprint comparison is conducted by fingerprint analysts. Minutiae are extracted from two fingerprint images and stored as point sets in the 2-dimensional plane. Minutiae-based matching mainly consists of gaining alignment between template and input minutiae sets which lead to the greatest number of minutiae pairs [5]. * _Pattern-based (image-based) matching_: This approach compares the basic fingerprint patterns (whorl, arch, and loop) between a candidate's fingerprint and the pre-stored template, which needs the fingerprint images to be aligned in the same direction. The employed algorithm detects a central point in the image for this reason. The template in the pattern-based matching algorithm contains the size, type, and orientation of the patterns in the alignment fingerprint image. The template image is compared graphically with the candidate to define the similarity degree. Most fingerprint patterns include arches, loops, and whorls. In the arch pattern, the ridges come in from one side, rise to form an arc in the middle, then out from the other side. In the loop pattern, the ridge comes in from one side, making a curve, and it enters from the same side.