A Novel Fingerprint Recognition System Using Lbp Fuzzy Features
نویسنده
چکیده
This paper presents a simple, but computationally efficient approach for fingerprint recognition. In this proposed approach fingerprint image is divided into windows of size 3 3 to extract the fuzzy features. The information at the center of the window is the product of information extracted using Local Binary Pattern (LBP) and fuzzy membership function. Maximization of mutual information between orientation extracted from the test and trainee images is used for alignment of fingerprint images. K-nearest neighbor (KNN) and Support Vector Machine (SVM) classifiers are used for matching on FVC2002 DB2_B databases. The experimental results shows that recognition rate of 97.8% are observed with SVM classifier.
منابع مشابه
Facial Expression Recognition Based on Structural Changes in Facial Skin
Facial expressions are the most powerful and direct means of presenting human emotions and feelings and offer a window into a persons’ state of mind. In recent years, the study of facial expression and recognition has gained prominence; as industry and services are keen on expanding on the potential advantages of facial recognition technology. As machine vision and artificial intelligence advan...
متن کاملFingerprint: DWT, SVD Based Enhancement and Significant Contrast for Ridges and Valleys Using Fuzzy Measures
The performance of the Fingerprint recognition system will be more accurate with respect of enhancement for the fingerprint images. In this paper we develop a novel method for Fingerprint image contrast enhancement technique based on the discrete wavelet transform (DWT) and singular value decomposition (SVD) has been proposed. This technique is compared with conventional image equalization tech...
متن کاملHumanoid Fingerprint Recognition based on Fuzzy Neural Network
Nowadays the computer speed is much faster than before, however well-trained humans are still the best pattern recognizer. In this paper we propose a fingerprint recognition method which is based on humanoid algorithms. Because fingerprint patterns are fuzzy in nature and ridge endings are changed easily by scars, we try to only use ridge bifurcation as fingerprints minutiae and also design a “...
متن کاملAn Efficient Biometric Multimodal Fingerprint and Iris using an SVM Classifier and Adaptive Neuro Fuzzy Inference System (ANFIS)
Recent times witnessed much advancement in the field of biometric and multimodal biometric fields. This is typically observed in the area, of security, privacy, and forensics. Even for the best of unimodal biometric systems, it is often not possible to achieve a higher recognition rate. Fusion of matching scores of multiple biometric traits is becoming more and more prevalent and is a very like...
متن کاملNew Fuzzy LBP Features for Face Recognition
There are many Local texture features each very in way they implement and each of the Algorithm trying improve the performance. An attempt is made in this paper to represent a theoretically very simple and computationally effective approach for face recognition. In our implementation the face image is divided into 3x3 sub-regions from which the features are extracted using the Local Binary Patt...
متن کامل