An efficient method for partial fingerprint recognition based on local binary pattern

2010 ◽  
Author(s):  
S. Malathi ◽  
C. Meena
Keyword(s):  
Efficient Method ◽  
Local Binary Pattern ◽  
Fingerprint Recognition ◽  
Partial Fingerprint

An Efficient Retinal Vessels Biometric Recognition System by Using Multi-Scale Local Binary Pattern Descriptor

2020 ◽  
Vol 10 (10) ◽  
pp. 2481-2489
Author(s):  
Muhammad Sheraz Arshad Malik ◽  
Qoseen Zahra ◽  
Imran Ullah Khan ◽  
Muhammad Awais ◽  
Gang Qiao
Keyword(s):  
Feature Extraction ◽  
Random Forest ◽  
Efficient Method ◽  
Large Scale ◽  
Local Binary Pattern ◽  
Evaluation Criteria ◽  
Recognition System ◽  
Suggested Approach ◽  
Multi Scale ◽  
Biometric Systems

Biometric systems are technically used for human recognition by identifying the unique features of an individual. Many security issues are found related to biometric systems such as voice, fingerprints, face, iris, signatures, etc., but the retina is a unique and efficient method to identify valid one. The aim of this paper is provided with an efficient method to recognize someone based on unique retina features. A proposed system based on retinal blood vessel pattern by using multi-scale local binary pattern (MSLBP) and random forest (Bagging tree) as feature extraction and classification. MSLBP is an efficient method to extracted features at six scales perpixel level, earlier work found the deficiency based on simple binary pattern with coverage of small areas and per-pixel level in the surrounding. MSLBP and random forest classifier suggested approach use for improving usability, perceivability, and sensitivity on large scale areas. It is the fastest method to get features accurately in an efficient way at every level of pixels. This method based on deep learning evaluation (criteria) parameter selection that provides more significant influence with sharp feature extraction on large scale areas based on seconds and improves the efficiency of images. MSLBP overcomes the problem of image sizing, pixel levels and efficiently provide accurate results.

scholarly journals Passive Forensics for Region Duplication Image Forgery Based on Harris Feature Points and Local Binary Patterns

2013 ◽  
Vol 2013 ◽  
pp. 1-12 ◽  
Author(s):  
Jie Zhao ◽  
Weifeng Zhao
Keyword(s):  
Efficient Method ◽  
Local Binary Pattern ◽  
Local Binary Patterns ◽  
Image Editing ◽  
Feature Points ◽  
Feature Vectors ◽  
Region Duplication ◽  
Software Packages ◽  
Passive Forensics ◽  
Ransac Algorithm

Nowadays the demand for identifying the authenticity of an image is much increased since advanced image editing software packages are widely used. Region duplication forgery is one of the most common and immediate tampering attacks which are frequently used. Several methods to expose this forgery have been developed to detect and locate the tampered region, while most methods do fail when the duplicated region undergoes rotation or flipping before being pasted. In this paper, an efficient method based on Harris feature points and local binary patterns is proposed. First, the image is filtered with a pixelwise adaptive Wiener method, and then dense Harris feature points are employed in order to obtain a sufficient number of feature points with approximately uniform distribution. Feature vectors for a circle patch around each feature point are extracted using local binary pattern operators, and the similar Harris points are matched based on their representation feature vectors using the BBF algorithm. Finally, RANSAC algorithm is employed to eliminate the possible erroneous matches. Experiment results demonstrate that the proposed method can effectively detect region duplication forgery, even when an image was distorted by rotation, flipping, blurring, AWGN, JPEG compression, and their mixed operations, especially resistant to the forgery with the flat area of little visual structures.

scholarly journals Uniform Local Binary Pattern for Fingerprint Liveness Detection in the Gaussian Pyramid

2018 ◽  
Vol 2018 ◽  
pp. 1-9 ◽  
Author(s):  
Yujia Jiang ◽  
Xin Liu
Keyword(s):  
Local Binary Pattern ◽  
Fingerprint Recognition ◽  
Svm Classifier ◽  
Liveness Detection ◽  
Gaussian Pyramid ◽  
Detection Approach ◽  
Fingerprint Liveness Detection ◽  
Recognition Systems ◽  
Uniform Local Binary Pattern ◽  
High Recognition Accuracy

Fingerprint recognition schemas are widely used in our daily life, such as Door Security, Identification, and Phone Verification. However, the existing problem is that fingerprint recognition systems are easily tricked by fake fingerprints for collaboration. Therefore, designing a fingerprint liveness detection module in fingerprint recognition systems is necessary. To solve the above problem and discriminate true fingerprint from fake ones, a novel software-based liveness detection approach using uniform local binary pattern (ULBP) in spatial pyramid is applied to recognize fingerprint liveness in this paper. Firstly, preprocessing operation for each fingerprint is necessary. Then, to solve image rotation and scale invariance, three-layer spatial pyramids of fingerprints are introduced in this paper. Next, texture information for three layers spatial pyramids is described by using uniform local binary pattern to extract features of given fingerprints. The accuracy of our proposed method has been compared with several state-of-the-art methods in fingerprint liveness detection. Experiments based on standard databases, taken from Liveness Detection Competition 2013 composed of four different fingerprint sensors, have been carried out. Finally, classifier model based on extracted features is trained using SVM classifier. Experimental results present that our proposed method can achieve high recognition accuracy compared with other methods.

Security and matching of partial fingerprint recognition systems

2004 ◽  
Author(s):  
Tsai-Yang Jea ◽  
Viraj S. Chavan ◽  
Venu Govindaraju ◽  
John K. Schneider
Keyword(s):  
Fingerprint Recognition ◽  
Recognition Systems ◽  
Partial Fingerprint

scholarly journals Quality Controlled Region-Based Partial Fingerprint Recognition

2018 ◽  
Author(s):  
Omid Zanganeh ◽  
Komal Komal ◽  
Nandita Bhattacharjee ◽  
David Albrecht ◽  
Bala Srinivasan
Keyword(s):  
Reference Points ◽  
Fingerprint Recognition ◽  
Sufficient Information ◽  
New Paradigm ◽  
Ridge Structure ◽  
Matching Process ◽  
Computationally Intensive ◽  
Partial Fingerprint ◽  
Global Similarity

The conventional method of fingerprint alignment using reference points does not work well for partial fingerprints due to the limited or non-availability of reference points. Moreover, matching of partial fingerprints using existing techniques is challenging as partial fingerprints lack enough distinguishing information. Even if fingerprints consists of sufficient information, the varying quality of different parts of fingerprint affects recognition process. In this paper, a new paradigm in the form of region-based approach that uses all available fingerprint ridge structure for aligning the fingerprints is proposed. Additionally, a new metric to compute individual local region similarity based on region’s quality, size and consistency of its neighbouring regions is proposed and used in deriving the global similarity for matching process. Although the proposed approach is computationally intensive, yet, the error rate is close to zero as the experimental results shows. The method is most suitable in applications where perfect identification is required such as forensic investigations.  

Sign in / Sign up

Export Citation Format

Share Document