The document presents various biometric system projects focusing on different identification methods such as behavioral biometrics, fingerprint identification, multimodal biometric systems, and others. Each project includes an abstract describing the methodology, algorithms, and experimental results demonstrating the effectiveness and accuracy of the respective biometric recognition techniques. Overall, the contributions aim to enhance security measures and improve identification performance across diverse biometric applications.

1. M.Phil Computer Science Biometric System Projects
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List Link : http://kasanpro.com/projects-list/m-phil-computer-science-biometric-system-projects
Title :Mimicry Attack on Strategy Based Behavioral Biometric
Language : C#
Project Link : http://kasanpro.com/p/c-sharp/mimicry-attack-strategy-based-behavioral-biometric
Abstract : Biometric security measures are becoming a popular approach to securing computer systems, computer
networks,as well as access to workplaces and recreational facilities. Unfortunately biometric systems can be a target
of impersonation attacks, making their security questionable. In this paper we concentrate on ways of spoofing
behavioral biometrics and analyze the types of spoofing attacks which can be employed against biometric systems.
The concept of strategy-based behavioral biometrics is introduced followed by our experimental results from spoofing
security systems based on strategy-based biometric technology. Finally an existing methodology is suggested to
counteract spoofing attacks against behavior-based biometric systems.
Title :A Framework for Efficient Finger Print Identification using a Minutiate Tree
Language : Matlab
Project Link : http://kasanpro.com/p/matlab/efficient-finger-print-identification-minutiate-tree
Abstract : Given the existence of large fingerprint databases,including distributed systems, the development of
algorithms for performing fast searches in them has become the important topic for biometric researchers. In this
paper, we propose a new indexing method for fingerprint templates consisting of a set of minutia points. In ontrast to
previously presented methods, our algorithm is tree-based and well addresses the efficiency needs of complex
(possibly distributed) systems. One large index tree is constructed and the enrolled templates are represented by the
leaves of the tree. The branches in the index tree correspond to different localconfigurations of minutia points.
Searching the index tree entails extracting local minutia neighborhoods of the test fingerprint and matching them
against tree nodes. Therefore, the search time does not depend on the number of enrolled fingerprint templates, but
only on the index tree configuration. This framework can be adapted for different tree-building parameters (feature
sets, indexing levels, bin boundaries) according to user requirements and different enrollment and searching
techniques can be applied to improve accuracy. We conduct a number of the experiments on Fingerprint Verification
Competition databases, as well as the databases of synthetically generated fingerprint templates. The experiments
confirm the ability of the proposed algorithm to find correct matches in the database and the minimum search time
requirements.
Title :A Person Authentication Approach using Score Level Fusion of Retina, Ear and Palmprint Biometrics
Language : Matlab
Project Link : http://kasanpro.com/p/matlab/person-authentication-score-level-fusion-retina-ear-palmprint-biometrics
Abstract : A multimodal biometric system for person authentication using three traita Retina , Ear and palmprint is
proposed. Our method involves feature extraction and feature matching of the above three traits , to provide an
efficient person authentication in highly secure areas. In order to enhance the recoginition accuracy, we have used a
fusion method that combines the matching scores of retina, plam: print and ear recognition systems. The validity of
our approach is then verified with experimental results. We have made a performance analysis using the image from
VARIA retina database, USTB ear database and CASIA palm print database. The experimental results show that our
proposed fusion method gives 98.2% recognition rate is higher than the unimodal approach.
Title :Iris Recognition Using Possibilistic Fuzzy Matching on Local Features
Language : Matlab
Project Link : http://kasanpro.com/p/matlab/iris-recognition-using-possibilistic-fuzzy-matching-local-features

2. Abstract : In this paper, we propose a novel possibilistic fuzzy matching strategy with invariant properties, which can
provide a robust and effective matching scheme for two sets of iris feature points. In addition, the nonlinear
normalization model is adopted to provide more accurate position before matching. Moreover, an effective iris
segmentation method is proposed to refine the detected inner and outer boundaries to smooth curves. For feature
extraction, the Gabor filters are adopted to detect the local feature points from the segmented iris image in the
Cartesian coordinate system and to generate a rotation-invariant descriptor for each detected point. After that, the
proposed matching algorithm is used to compute a similarity score for two sets of feature points from a pair of iris
images. The experimental results show that the performance of our system is better than those of the systems based
on the local features and is comparable to those of the typical systems.
Title :Contact-free hand geometry-based identification system
Language : Matlab
Project Link : http://kasanpro.com/p/matlab/contact-free-hand-geometry-based-identification-system
Abstract : This paper presents an approach for personal identification using hand geometrical features, in which the
infrared illumination device is employed to improve the usability of this hand recognition system. In the proposed
system, prospective users can place their hand freely in front of the camera without any pegs or templates. Moreover,
the proposed system can be widely used under dark environment and complex background scenarios. To achieve
better detection accuracy, in total 13 important points are detected from a palm image, and 34 features calculated
from these points are used to further recognition. Experimental results demonstrate that the averaged Correct
Identification Rate (CIR) is 96.23% and averaged False Accept Rate (FAR) is 1.85%. These results prove that the
proposed contact-free system can be considered as an effective identity verification system for practical applications.
M.Phil Computer Science Biometric System Projects
Title :Human Identification using Finger Images
Language : Matlab
Project Link : http://kasanpro.com/p/matlab/human-identification-finger-images
Abstract : This paper presents a new approach to improve the performance of finger vein identification systems
presented in the literature. The proposed system simultaneously acquires the finger vein and low resolution fingerprint
images and combines these two evidences using novel score level combination strategy. We examine the previously
proposed finger vein identification approaches and develop a new approach that illustrates it superiority over prior
published efforts. The utility of low resolution fingerprint images acquired from a webcam is examined to ascertain the
matching performance from such images. We develop and investigate two new score level combinations, i.e., holistic
and nonlinear fusion, and comparatively evaluate them with more popular score level fusion approaches to ascertain
their effectiveness in proposed system. The rigorous experimental results presented on the database of 6,264 images
from 156 subjects illustrate significant improvement in the performance, both from the authentication and recognition
experiments.
Title :Iris Data Indexing Method Using Gabor Energy Features
Language : Matlab
Project Link : http://kasanpro.com/p/matlab/iris-data-indexing-method-using-gabor-energy-features
Abstract : Biometric features are extracted from a complex pattern and stored as high dimensional data. These data
do not follow traditional sorting order like numerical and alphabetical data. Hence, a linear search method makes the
identification process extremely slow as well as increases the false acceptance rate beyond an acceptable range. To
address this problem, we propose an efficient indexing mechanism to retrieve iris biometric templates using Gabor
energy features. The Gabor energy features are calculated from the preprocessed iris texture in different scales and
orientations to generate a 12-dimensional index key for an iris template. An index space is created based on the
values of index keys of all individuals. A candidate set is retrieved from the index space based on the values of query
index key. Next, we rank the retrieved candidates according to their occurrences. If the identity of the query template
is matched, then it is a hit, otherwise a miss. We have experimented our approach with Bath, CASIA-V3-In- terval,
CASIA-V4-Thousand, MMU2, and WVU iris databases. Our proposed approach gives 11.3%, 14.5%, 16.3%, 13.5%,
and 10.3% penetration rates and 98.2%, 91.1%, 90.7%, 85.2%, and 96% hit rates for Bath, CASIA-V3-Interval,
CASIA-V4-Thousand, MMU2, and WVU iris database, respectively, when we consider the retrieving templates up to
the fifth rank. Experiments substantiate that our approach is capable of retrieving biometric data with a higher hit rate
and lower penetration rate compared to the existing approaches. Application of Gabor energy features to index iris
data proves to be effective for fast and accurate retrieval. With our proposed approach, it is possible to retrieve a set
of iris templates similar to the query template in the order of milliseconds and is independent of sizes of databases.

3. Title :An Embedded Real-Time Finger-Vein Recognition System for Mobile Devices
Language : Matlab
Project Link : http://kasanpro.com/p/matlab/finger-vein-recognition-system-mobile-devices
Abstract : With the development of consumer electronics, the demand for simple, convenient, and high-security
authentication systems for protecting private information stored in mobile devices has steadily increased. In
consideration of emerging requirements for information protection, biometrics, which uses human physiological or
behavioral features for personal identification, has been extensively studied as a solution to security issues. However,
most existing biometric systems have high complexity in time or space or both, and are thus not suitable for mobile
devices. In this paper, we propose a real-time embedded finger-vein recognition system for authentication on mobile
devices. The system is implemented on a DSP platform and equipped with a novel finger-vein recognition algorithm.
The proposed system takes only about 0.8 seconds to verify one input finger vein sample and achieves an equal error
rate (EER) of 0.07 on a database of 100 subjects. The experimental results demonstrate that the proposed finger-vein
recognition system is qualified for authentication on mobile devices.
http://kasanpro.com/ieee/final-year-project-center-tiruchchirappalli-reviews
Title :Palm-Print Classification by Global Features
Language : Matlab
Project Link : http://kasanpro.com/p/matlab/palm-print-classification-global-features
Abstract : Three-dimensional 3D palm print has proved to be a significant biometrics for personal authentication.
Three- dimensional palm prints are harder to counterfeit than 2D palm prints and more robust to variations in
illumination and serious scrabbling on the palm surface. Previous work on 3D palm-print recognition has concentrated
on local features such as texture and lines. In this paper, we propose three novel global features of 3D palm prints
which describe shape information and can be used for coarse matching and indexing to improve the efficiency of
palm-print recognition, particularly in very large databases. The three proposed shape features are maximum depth of
palm center, horizontal cross-sectional area of different levels, and radial line length from the centroid to the boundary
of 3D palm-print horizontal cross section of different levels. We treat these features as a column vector and use
orthogonal linear discriminant analysis to reduce their dimensionality. We then adopt two schemes 1. coarse-level
matching and 2. ranking support vector machine to improve the efficiency of palmprint recognition. We conducted a
series of 3D palm-print recognition experiments using an established 3D palm-print database, and the results
demonstrate that the proposed method can greatly reduce penetration rates.
Title :Video-based Face Recognition Technology for Automotive Security
Language : Matlab
Project Link : http://kasanpro.com/p/matlab/video-based-face-recognition-technology-automotive-security
Abstract : In this paper, face recognition technology is applied to automotive security. Because the face system is
totally non-intrusive, it can therefore make an existing security system more effective without bothering the user in any
way. This paper introduce a video-based face recognition systems for auto security, and describe the face recognition
systems and algorithm in detail.
M.Phil Computer Science Biometric System Projects
Title :Palm - Print Recognition by 2D and 3D Features
Language : Matlab
Project Link : http://kasanpro.com/p/matlab/palm-print-recognition-2d-3d-features
Abstract : Palmprint recognition has now been a hot topic of research in the biometric system. Previous works are
focused on 3D and 2D features of palmprint as a separate research. Here we proposed an multi feature of palmprints
by the combination of 3D feature and 2D features. In this paper we propose three features of 3D palmprints and one
feature of 2D palmprint. They are maximum depth (MD), horizontal cross sectional area (HCA), radial line length
(RLL) and ridge minutiae. Then the classification of palmprints are made by support vector machine and euclidean
distance metrics.