Developmentof Image Enhancement and the Feature Extraction Techniques on Rural Fingerprint Images to Improve the Recognition and the Authentication Rate.
Abstract: Fingerprint recognition is one of the most popular and successful methods used for person
identification which takes advantage of the fact that the fingerprint has some unique characteristics called
minutiae which are points where a extracts the ridges and bifurcation from a fingerprint image. A critical step in
studying the statistics of fingerprint minutiae is to reliably extract minutiae from the fingerprint images.
However fingerprint images are rarely of perfect quality. Fingerprint image enhancement techniques are
employed prior to minutiae extraction to obtain a more reliable estimation of minutiae locations.
Fingerprint matching is often affected by the presence of intrinsically low quality fingerprints and various
distortions introduced during the acquisition process. In this paper we have used the rural fingerprints
database which is collected from IIIT Delhi research lab which consists of 1634 fingerprints images. Out of
which we have preprocess 600 sample preprocessing extracts the ridges and bifurcation from a fingerprint
image and tried to improve the quality of images. The Resultant images quality is verified by using different
quality measures.
Keywords: minutiae extraction, extracts the ridges and bifurcation, rural fingerprint authentication.
International Journal of Engineering and Science Invention (IJESI)inventionjournals
International Journal of Engineering and Science Invention (IJESI) is an international journal intended for professionals and researchers in all fields of computer science and electronics. IJESI publishes research articles and reviews within the whole field Engineering Science and Technology, new teaching methods, assessment, validation and the impact of new technologies and it will continue to provide information on the latest trends and developments in this ever-expanding subject. The publications of papers are selected through double peer reviewed to ensure originality, relevance, and readability. The articles published in our journal can be accessed online.
This paper introduces the implementation of fingerprint matching Minutiae Algorithm for Fingerprint
Matching. These algorithm increases the reliability accuracy of the fingerprint matching. The proposed method was
evaluated by means of experiment conducted on the FVC2002, FVC2004 database. Experimental results confirm
that the taking time of the fingerprint image matching is very less than the other methods. This algorithm is very
effective algorithm for the identification of fingerprint image.
Fingerprint Minutiae Extraction and Compression using LZW Algorithmijsrd.com
For security and surveillance automated personal identification is major issue. We can see a lot varieties of biometric systems like face detection, fingerprint recognition, iris recognition, voice recognition, palm recognition etc. In our project we will only go for fingerprint recognition. Never two peoples have exactly same fingerprints even twins, they are totally unique. The sensors capture the finger prints of humans and convert them into images and a minutiae extraction algorithm extracts the location of minutiae points called termination and bifurcation. A database system stores these patterns and minutiae points of fingerprint. A large storage space required to store bifurcation and termination points for the fingerprint database. LZW compression algorithm has been used to reduce the size of data. With LZW applied on these extracted minutiae points, these minutiae points get encoded which add more security feature.
Hybrid fingerprint matching algorithm for high accuracy and reliabilityeSAT Publishing House
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology.
International Journal of Computational Engineering Research(IJCER)ijceronline
International Journal of Computational Engineering Research(IJCER) is an intentional online Journal in English monthly publishing journal. This Journal publish original research work that contributes significantly to further the scientific knowledge in engineering and Technology.
Experimental study of minutiae based algorithm for fingerprint matchingcsandit
In this paper, a minutiae-based algorithm for fingerprint pattern recognition and matching is
proposed. The algorithm uses the distance between the minutiae and core points to determine
the pattern matching scores for fingerprint images. Experiments were conducted using
FVC2002 fingerprint database comprising four datasets of images of different sources and
qualities. False Match Rate (FMR), False Non-Match Rate (FNMR) and the Average Matching
Time (AMT) were the statistics generated for testing and measuring the performance of the
proposed algorithm. The comparative analysis of the proposed algorithm and some existing
minutiae based algorithms was carried out as well. The findings from the experimental study
were presented, interpreted and some conclusions were drawn.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
International Journal of Engineering and Science Invention (IJESI)inventionjournals
International Journal of Engineering and Science Invention (IJESI) is an international journal intended for professionals and researchers in all fields of computer science and electronics. IJESI publishes research articles and reviews within the whole field Engineering Science and Technology, new teaching methods, assessment, validation and the impact of new technologies and it will continue to provide information on the latest trends and developments in this ever-expanding subject. The publications of papers are selected through double peer reviewed to ensure originality, relevance, and readability. The articles published in our journal can be accessed online.
This paper introduces the implementation of fingerprint matching Minutiae Algorithm for Fingerprint
Matching. These algorithm increases the reliability accuracy of the fingerprint matching. The proposed method was
evaluated by means of experiment conducted on the FVC2002, FVC2004 database. Experimental results confirm
that the taking time of the fingerprint image matching is very less than the other methods. This algorithm is very
effective algorithm for the identification of fingerprint image.
Fingerprint Minutiae Extraction and Compression using LZW Algorithmijsrd.com
For security and surveillance automated personal identification is major issue. We can see a lot varieties of biometric systems like face detection, fingerprint recognition, iris recognition, voice recognition, palm recognition etc. In our project we will only go for fingerprint recognition. Never two peoples have exactly same fingerprints even twins, they are totally unique. The sensors capture the finger prints of humans and convert them into images and a minutiae extraction algorithm extracts the location of minutiae points called termination and bifurcation. A database system stores these patterns and minutiae points of fingerprint. A large storage space required to store bifurcation and termination points for the fingerprint database. LZW compression algorithm has been used to reduce the size of data. With LZW applied on these extracted minutiae points, these minutiae points get encoded which add more security feature.
Hybrid fingerprint matching algorithm for high accuracy and reliabilityeSAT Publishing House
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology.
International Journal of Computational Engineering Research(IJCER)ijceronline
International Journal of Computational Engineering Research(IJCER) is an intentional online Journal in English monthly publishing journal. This Journal publish original research work that contributes significantly to further the scientific knowledge in engineering and Technology.
Experimental study of minutiae based algorithm for fingerprint matchingcsandit
In this paper, a minutiae-based algorithm for fingerprint pattern recognition and matching is
proposed. The algorithm uses the distance between the minutiae and core points to determine
the pattern matching scores for fingerprint images. Experiments were conducted using
FVC2002 fingerprint database comprising four datasets of images of different sources and
qualities. False Match Rate (FMR), False Non-Match Rate (FNMR) and the Average Matching
Time (AMT) were the statistics generated for testing and measuring the performance of the
proposed algorithm. The comparative analysis of the proposed algorithm and some existing
minutiae based algorithms was carried out as well. The findings from the experimental study
were presented, interpreted and some conclusions were drawn.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Enhanced Thinning Based Finger Print RecognitionIJCI JOURNAL
This paper is the implementation of fingerprint recognition system in which the matching is done using the
Minutiae points. The methodology is the extracting & applying matching procedure on the Minutiae points
between the sample fingerprint & fingerprint under question. The main functional blocks of this system
follows steps of Image Thinning, Image Segmentation, Minutiae (feature) point Extraction, & Minutiae
point Matching. The procedure of Enhanced Thinning included for the purpose of decreasing the size of the
memory space used by the fingerprint image database.
Biometric system works on behavioral and physiological biometric parameters to spot a person. Every fingerprint contains distinctive options and its recognizing system primarily works on native ridge feature local ridge endings, minutiae, core point, delta, etc. However, fingerprint pictures have poor quality thanks to variations in skin and impression conditions. In personal identification, fingerprint recognition is taken into account the foremost outstanding and reliable technique for matching with keep fingerprints within the information. Minutiae extraction is additional essential step in fingerprint matching. This paper provides plan regarding numerous feature extraction and matching algorithms for fingerprint recognition systems and to seek out that technique is additional reliable and secure.
An efficient method for recognizing the low quality fingerprint verification ...IJCI JOURNAL
In this paper, we propose an efficient method to provide personal identification using fingerprint to get better accuracy even in noisy condition. The fingerprint matching based on the number of corresponding minutia pairings, has been in use for a long time, which is not very efficient for recognizing the low quality fingerprints. To overcome this problem, correlation technique is used. The correlation-based fingerprint verification system is capable of dealing with low quality images from which no minutiae can be extracted reliably and with fingerprints that suffer from non-uniform shape distortions, also in case of damaged and partial images. Orientation Field Methodology (OFM) has been used as a preprocessing module, and it converts the images into a field pattern based on the direction of the ridges, loops and bifurcations in the image of a fingerprint. The input image is then Cross Correlated (CC) with all the images in the cluster and the highest correlated image is taken as the output. The result gives a good recognition rate, as the proposed scheme uses Cross Correlation of Field Orientation (CCFO = OFM + CC) for fingerprint identification.
Enhancing Security and Privacy Issue in Airport by Biometric based Iris Recog...idescitation
Few years ago a self service has been predominant way of passenger at airport.
For the passenger that is a very enjoyable and comfort situation because it keeps control
over all process during their complete journey. For airport and for airlines is also very
interesting evolution because self service allows increasing capacity of airport without any
significant extra investment. However success of self service induces one potential risk. That
is of lack of human contact between airline operator and passenger, there is a problem in
identifying a passenger. This is definitely the problem for immigrations forcibly. This
potential risk of the industry is needed to be addressed and biometrics definitely can solve
this kind of problem. Nowadays biometric is considered to be the most important and
reliable method for personal identification. Iris recognition is considered as most personal
identification.
PREPROCESSING ALGORITHM FOR DIGITAL FINGERPRINT IMAGE RECOGNITION ijcsity
Biometrics is one of the most used technologies in the field of security due to its reliability and
performance. It is based on several physical human characteristics but the most used technology is the
fingerprint recognition, and since we must carry out an image processing to be able to exploit the data in
each fingerprint we propose in this article an image preprocessing procedure in order to improve its
quality before extracting the necessary information for the comparison phase.
ABSTRACT Feature extraction plays a vital role in the analysis and interpretation of remotely sensed data. The two important components of Feature extraction are Image enhancement and information extraction. Image enhancement techniques help in improving the visibility of any portion or feature of the image. Information extraction techniques help in obtaining the statistical information about any particular feature or portion of the image. This presented work focuses on the various feature extraction techniques and area of optical character recognition is a particularly important in Image processing. Keywords— Image character recognition, Methods for Feature Extraction, Basic Gabor Filter, IDA, and PCA.
Fingerprint Registration Using Zernike Moments : An Approach for a Supervised...CSCJournals
In this work, we deal with contactless fingerprint biometrics. More specifically, we are interested in solving the problem of registration by taking into consideration some constraints such as finger rotation and translation. In the proposed method, the registration requires: (1) a segmentation technique to extract streaks, (2) a skeletonization technique to extract the center line streaks and (3) and landmarks extraction technique. The correspondence between the sets of control points, is obtained by calculating the descriptor vector of Zernike moments on a window of size RxR centered at each point. Comparison of correlation coefficients between the descriptor vectors of Zernike moments helps define the corresponding points. The estimation of parameters of the existing deformation between images is performed using RANSAC algorithm (Random SAmple Consensus) that suppresses wrong matches. Finally, performance evaluation is achieved on a set of fingerprint images where promising results are reported.
Vision based human computer interface using colour detectioneSAT Journals
Abstract In this paper we have tried to present an approach to Human Computer Interaction (HCI). Here we have tried to control actions
associated with mouse. Each mouse actions are associated to a colour pointer. These colour pointer are acquired as input using
web camera. The acquired colour pointer are processed using colour detection technique.
Keywords: Human Computer Interaction, Web Camera, Colour Detection, Colour Subtraction.
This paper presents the maneuver of mouse pointer and performs various mouse operations such as left
click, right click, double click, drag etc using gestures recognition technique. Recognizing gestures is a
complex task which involves many aspects such as motion modeling, motion analysis, pattern recognition
and machine learning.
Keeping all the essential factors in mind a system has been created which recognizes the movement of
fingers and various patterns formed by them. Color caps have been used for fingers to distinguish it from
the background color such as skin color. Thus recognizing the gestures various mouse events have been
performed. The application has been created on MATLAB environment with operating system as windows
7.
Enhanced Thinning Based Finger Print RecognitionIJCI JOURNAL
This paper is the implementation of fingerprint recognition system in which the matching is done using the
Minutiae points. The methodology is the extracting & applying matching procedure on the Minutiae points
between the sample fingerprint & fingerprint under question. The main functional blocks of this system
follows steps of Image Thinning, Image Segmentation, Minutiae (feature) point Extraction, & Minutiae
point Matching. The procedure of Enhanced Thinning included for the purpose of decreasing the size of the
memory space used by the fingerprint image database.
Biometric system works on behavioral and physiological biometric parameters to spot a person. Every fingerprint contains distinctive options and its recognizing system primarily works on native ridge feature local ridge endings, minutiae, core point, delta, etc. However, fingerprint pictures have poor quality thanks to variations in skin and impression conditions. In personal identification, fingerprint recognition is taken into account the foremost outstanding and reliable technique for matching with keep fingerprints within the information. Minutiae extraction is additional essential step in fingerprint matching. This paper provides plan regarding numerous feature extraction and matching algorithms for fingerprint recognition systems and to seek out that technique is additional reliable and secure.
An efficient method for recognizing the low quality fingerprint verification ...IJCI JOURNAL
In this paper, we propose an efficient method to provide personal identification using fingerprint to get better accuracy even in noisy condition. The fingerprint matching based on the number of corresponding minutia pairings, has been in use for a long time, which is not very efficient for recognizing the low quality fingerprints. To overcome this problem, correlation technique is used. The correlation-based fingerprint verification system is capable of dealing with low quality images from which no minutiae can be extracted reliably and with fingerprints that suffer from non-uniform shape distortions, also in case of damaged and partial images. Orientation Field Methodology (OFM) has been used as a preprocessing module, and it converts the images into a field pattern based on the direction of the ridges, loops and bifurcations in the image of a fingerprint. The input image is then Cross Correlated (CC) with all the images in the cluster and the highest correlated image is taken as the output. The result gives a good recognition rate, as the proposed scheme uses Cross Correlation of Field Orientation (CCFO = OFM + CC) for fingerprint identification.
Enhancing Security and Privacy Issue in Airport by Biometric based Iris Recog...idescitation
Few years ago a self service has been predominant way of passenger at airport.
For the passenger that is a very enjoyable and comfort situation because it keeps control
over all process during their complete journey. For airport and for airlines is also very
interesting evolution because self service allows increasing capacity of airport without any
significant extra investment. However success of self service induces one potential risk. That
is of lack of human contact between airline operator and passenger, there is a problem in
identifying a passenger. This is definitely the problem for immigrations forcibly. This
potential risk of the industry is needed to be addressed and biometrics definitely can solve
this kind of problem. Nowadays biometric is considered to be the most important and
reliable method for personal identification. Iris recognition is considered as most personal
identification.
PREPROCESSING ALGORITHM FOR DIGITAL FINGERPRINT IMAGE RECOGNITION ijcsity
Biometrics is one of the most used technologies in the field of security due to its reliability and
performance. It is based on several physical human characteristics but the most used technology is the
fingerprint recognition, and since we must carry out an image processing to be able to exploit the data in
each fingerprint we propose in this article an image preprocessing procedure in order to improve its
quality before extracting the necessary information for the comparison phase.
ABSTRACT Feature extraction plays a vital role in the analysis and interpretation of remotely sensed data. The two important components of Feature extraction are Image enhancement and information extraction. Image enhancement techniques help in improving the visibility of any portion or feature of the image. Information extraction techniques help in obtaining the statistical information about any particular feature or portion of the image. This presented work focuses on the various feature extraction techniques and area of optical character recognition is a particularly important in Image processing. Keywords— Image character recognition, Methods for Feature Extraction, Basic Gabor Filter, IDA, and PCA.
Fingerprint Registration Using Zernike Moments : An Approach for a Supervised...CSCJournals
In this work, we deal with contactless fingerprint biometrics. More specifically, we are interested in solving the problem of registration by taking into consideration some constraints such as finger rotation and translation. In the proposed method, the registration requires: (1) a segmentation technique to extract streaks, (2) a skeletonization technique to extract the center line streaks and (3) and landmarks extraction technique. The correspondence between the sets of control points, is obtained by calculating the descriptor vector of Zernike moments on a window of size RxR centered at each point. Comparison of correlation coefficients between the descriptor vectors of Zernike moments helps define the corresponding points. The estimation of parameters of the existing deformation between images is performed using RANSAC algorithm (Random SAmple Consensus) that suppresses wrong matches. Finally, performance evaluation is achieved on a set of fingerprint images where promising results are reported.
Vision based human computer interface using colour detectioneSAT Journals
Abstract In this paper we have tried to present an approach to Human Computer Interaction (HCI). Here we have tried to control actions
associated with mouse. Each mouse actions are associated to a colour pointer. These colour pointer are acquired as input using
web camera. The acquired colour pointer are processed using colour detection technique.
Keywords: Human Computer Interaction, Web Camera, Colour Detection, Colour Subtraction.
This paper presents the maneuver of mouse pointer and performs various mouse operations such as left
click, right click, double click, drag etc using gestures recognition technique. Recognizing gestures is a
complex task which involves many aspects such as motion modeling, motion analysis, pattern recognition
and machine learning.
Keeping all the essential factors in mind a system has been created which recognizes the movement of
fingers and various patterns formed by them. Color caps have been used for fingers to distinguish it from
the background color such as skin color. Thus recognizing the gestures various mouse events have been
performed. The application has been created on MATLAB environment with operating system as windows
7.
LATENT FINGERPRINT MATCHING USING AUTOMATED FINGERPRINT IDENTIFICATION SYSTEM
Similar to Developmentof Image Enhancement and the Feature Extraction Techniques on Rural Fingerprint Images to Improve the Recognition and the Authentication Rate.
"FingerPrint Recognition Using Principle Component Analysis(PCA)”Er. Arpit Sharma
Fingerprint recognition is one of the oldest and most popular biometric technologies and it is used in criminal investigations, civilian, commercial applications, and so on. Fingerprint matching is the process used to determine whether the two sets of fingerprints details come from the same finger or not. This work focuses on feature extraction and minutiae matching stage. There are many matching techniques used for fingerprint recognition systems such as minutiae based matching, pattern based matching, Correlation based matching, and image based matching.
A new method based upon Principal Component Analysis (PCA) for fingerprint enhancement is proposed in this paper. PCA is a useful statistical technique that has found application in fields such as face recognition and image compression, and is a common technique for finding patterns in data of high dimension. In the proposed method image is first decomposed into directional images using decimation free Directional Filter bank DDFB. Then PCA is applied to these directional fingerprint images which gives the PCA filtered images. Which are basically directional images? Then these directional images are reconstructed into one image which is the enhanced one. Simulation results are included illustrating the capability of the proposed method.
Review of Various Image Processing Techniques for Currency Note AuthenticationIJCERT
In cash transactions, the biggest challenge faced is counterfeit notes. This problem is only expanding due to the technology available and many fraud cases have been uncovered. Manual detection of counterfeit notes is time consuming and inefficient and hence the need of automated counterfeit detection has raised. To tackle this problem, we studied existing systems using Matlab, which used different methods to detect fake notes.
GANNON UNIVERSITY
ELECTRICAL AND COMPUTER ENGINEERING DEPARTMENT
FALL2015
GECE 572: DIGITAL SIGNAL PROCESSING
FINGER PRINT RECOGNITION USING MINUTIAE BASED FEATURE
FINAL PROJECT
Prepared by
THADASINA PRUTHVIN REDDY
[email protected]
SALMAN SIDDIQUI
[email protected]
Instructor:
Dr. Ram Sundaram
Table of contents
1. Abstract
2. Introduction
3. Fingerprint matching
4. Pre-processing stage
5. Minutiae extraction stage
6. Post-processing stage
7. Merits & Demerits
8. Applications & future scope
9. Conclusions
10.References
1. Abstract
Nowadays, conventional identification methods such as driver's license, passport, ATM cards and PIN codes do not meet the demands of this wide scale connectivity. Automated biometrics in general, and automated fingerprint authentication in particular, provide efficient solutions to these modern identification problems. Fingerprints have been used for many centuries as a means of identifying people. The fingerprints of individual are unique and are stay unchanged during the life time. Fingerprint matching techniques can be placed into two categories, minutiae-based and correlation based. Minutiae-based techniques first find minutiae points and then map their relative placement on the finger. However, there are some difficulties when using this approach. It is difficult to extract the minutiae points accurately when the fingerprint is of low quality the correlation-based method is able to overcome some of the difficulties of the minutiae-based approach. However, it has some of its own shortcomings. Correlation-based techniques require the precise location of a registration point and are affected by image translation and rotation.
2. Introduction
Biometric recognition refers to the use of distinctive physiological (e.g. fingerprint, palm print, iris, face) and behavioral (e.g. gait, signature) characteristics, called biometric identifiers for recognizing individuals.
Fingerprint recognition is one of the oldest and most reliable biometric used for personal identification. Fingerprint recognition has been used for over 100 years now and has come a long way from tedious manual fingerprint matching. The ancient procedure of matching fingerprints manually was extremely cumbersome and time-consuming and required skilled personnel.
Finger skin is made up of friction ridges and sweat pores all along these ridges. Friction ridges are created during fetal life and only the general shape is genetically defined. The distinguishing nature of physical characteristics of a person is due to both the inherent individual genetic diversity within the human population as well as the random processes affecting the development of the embryo. Friction ridges ...
Enhanced Thinning Based Finger Print RecognitionIJCI JOURNAL
This paper is the implementation of fingerprint recognition system in which the matching is done using the Minutiae points. The methodology is the extracting & applying matching procedure on the Minutiae points between the sample fingerprint & fingerprint under question. The main functional blocks of this system follows steps of Image Thinning, Image Segmentation, Minutiae (feature) point Extraction, & Minutiae point Matching. The procedure of Enhanced Thinning included for the purpose of decreasing the size of the memory space used by the fingerprint image database.
Biometric is a technology which deals with unique bio elements of an individual.
It is used to verify an individual by its own bio elements saved in system.
Generate a key for MAC Algorithm using Biometric Fingerprint ijasuc
known as cryptographic checksum or MAC that is appended to the message.
The unauthorized thefts in our society have made the requirement for reliable information security
mechanisms. Information security can be accomplished with the help of a prevailing tool like cryptography,
protecting the cryptographic keys is one of the significant issues to be deal with. Here we proposed a
biometric-crypto system which generates a cryptographic key from the Finger prints for calculating the
MAC value of the information we considered fingerprint because it is unique and permanent through out a
person’s life.
PREPROCESSING ALGORITHM FOR DIGITAL FINGERPRINT IMAGE RECOGNITIONijcsity
Biometrics is one of the most used technologies in the field of security due to its reliability and
performance. It is based on several physical human characteristics but the most used technology is the
fingerprint recognition, and since we must carry out an image processing to be able to exploit the data in
each fingerprint we propose in this article an image preprocessing procedure in order to improve its
quality before extracting the necessary information for the comparison phase
PREPROCESSING ALGORITHM FOR DIGITAL FINGERPRINT IMAGE RECOGNITIONijcsity
Biometrics is one of the most used technologies in the field of security due to its reliability and performance. It is based on several physical human characteristics but the most used technology is the fingerprint recognition, and since we must carry out an image processing to be able to exploit the data in each fingerprint we propose in this article an image preprocessing procedure in order to improve its quality before extracting the necessary information for the comparison phase.
Advanced Authentication Scheme using Multimodal Biometric SchemeEditor IJCATR
Fingerprint recognition has attracted various researchers and achieved great success. But, fingerprint alone may not be able to meet the increasing demand of high accuracy in today‟s biometric system. The purpose of our paper is to inspect whether the integration of palmprint and fingerprint biometric can achieve performance that may not be possible using a single biometric technology. Pre-processing is done for fingerprint and palmprint images separately in order to remove any noise. The next step is feature extraction. Minutiae algorithm is used for fingerprint feature extraction and Local Binary pattern for palmprint. Wavelet fusion is applied in order to fuse the extracted features and Support Vector Machine is used for matching. The main highlight of the project is multimodal biometrics which will give a better security and accuracy comparing to unimodel system.
An Enhanced Authentication System Using Face and Fingerprint Technologiesiosrjce
IOSR Journal of Computer Engineering (IOSR-JCE) is a double blind peer reviewed International Journal that provides rapid publication (within a month) of articles in all areas of computer engineering and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications in computer technology. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
Similar to Developmentof Image Enhancement and the Feature Extraction Techniques on Rural Fingerprint Images to Improve the Recognition and the Authentication Rate. (20)
Adaptive synchronous sliding control for a robot manipulator based on neural ...IJECEIAES
Robot manipulators have become important equipment in production lines, medical fields, and transportation. Improving the quality of trajectory tracking for
robot hands is always an attractive topic in the research community. This is a
challenging problem because robot manipulators are complex nonlinear systems
and are often subject to fluctuations in loads and external disturbances. This
article proposes an adaptive synchronous sliding control scheme to improve trajectory tracking performance for a robot manipulator. The proposed controller
ensures that the positions of the joints track the desired trajectory, synchronize
the errors, and significantly reduces chattering. First, the synchronous tracking
errors and synchronous sliding surfaces are presented. Second, the synchronous
tracking error dynamics are determined. Third, a robust adaptive control law is
designed,the unknown components of the model are estimated online by the neural network, and the parameters of the switching elements are selected by fuzzy
logic. The built algorithm ensures that the tracking and approximation errors
are ultimately uniformly bounded (UUB). Finally, the effectiveness of the constructed algorithm is demonstrated through simulation and experimental results.
Simulation and experimental results show that the proposed controller is effective with small synchronous tracking errors, and the chattering phenomenon is
significantly reduced.
Low power architecture of logic gates using adiabatic techniquesnooriasukmaningtyas
The growing significance of portable systems to limit power consumption in ultra-large-scale-integration chips of very high density, has recently led to rapid and inventive progresses in low-power design. The most effective technique is adiabatic logic circuit design in energy-efficient hardware. This paper presents two adiabatic approaches for the design of low power circuits, modified positive feedback adiabatic logic (modified PFAL) and the other is direct current diode based positive feedback adiabatic logic (DC-DB PFAL). Logic gates are the preliminary components in any digital circuit design. By improving the performance of basic gates, one can improvise the whole system performance. In this paper proposed circuit design of the low power architecture of OR/NOR, AND/NAND, and XOR/XNOR gates are presented using the said approaches and their results are analyzed for powerdissipation, delay, power-delay-product and rise time and compared with the other adiabatic techniques along with the conventional complementary metal oxide semiconductor (CMOS) designs reported in the literature. It has been found that the designs with DC-DB PFAL technique outperform with the percentage improvement of 65% for NOR gate and 7% for NAND gate and 34% for XNOR gate over the modified PFAL techniques at 10 MHz respectively.
A review on techniques and modelling methodologies used for checking electrom...nooriasukmaningtyas
The proper function of the integrated circuit (IC) in an inhibiting electromagnetic environment has always been a serious concern throughout the decades of revolution in the world of electronics, from disjunct devices to today’s integrated circuit technology, where billions of transistors are combined on a single chip. The automotive industry and smart vehicles in particular, are confronting design issues such as being prone to electromagnetic interference (EMI). Electronic control devices calculate incorrect outputs because of EMI and sensors give misleading values which can prove fatal in case of automotives. In this paper, the authors have non exhaustively tried to review research work concerned with the investigation of EMI in ICs and prediction of this EMI using various modelling methodologies and measurement setups.
Hierarchical Digital Twin of a Naval Power SystemKerry Sado
A hierarchical digital twin of a Naval DC power system has been developed and experimentally verified. Similar to other state-of-the-art digital twins, this technology creates a digital replica of the physical system executed in real-time or faster, which can modify hardware controls. However, its advantage stems from distributing computational efforts by utilizing a hierarchical structure composed of lower-level digital twin blocks and a higher-level system digital twin. Each digital twin block is associated with a physical subsystem of the hardware and communicates with a singular system digital twin, which creates a system-level response. By extracting information from each level of the hierarchy, power system controls of the hardware were reconfigured autonomously. This hierarchical digital twin development offers several advantages over other digital twins, particularly in the field of naval power systems. The hierarchical structure allows for greater computational efficiency and scalability while the ability to autonomously reconfigure hardware controls offers increased flexibility and responsiveness. The hierarchical decomposition and models utilized were well aligned with the physical twin, as indicated by the maximum deviations between the developed digital twin hierarchy and the hardware.
Literature Review Basics and Understanding Reference Management.pptxDr Ramhari Poudyal
Three-day training on academic research focuses on analytical tools at United Technical College, supported by the University Grant Commission, Nepal. 24-26 May 2024
Understanding Inductive Bias in Machine LearningSUTEJAS
This presentation explores the concept of inductive bias in machine learning. It explains how algorithms come with built-in assumptions and preferences that guide the learning process. You'll learn about the different types of inductive bias and how they can impact the performance and generalizability of machine learning models.
The presentation also covers the positive and negative aspects of inductive bias, along with strategies for mitigating potential drawbacks. We'll explore examples of how bias manifests in algorithms like neural networks and decision trees.
By understanding inductive bias, you can gain valuable insights into how machine learning models work and make informed decisions when building and deploying them.
CHINA’S GEO-ECONOMIC OUTREACH IN CENTRAL ASIAN COUNTRIES AND FUTURE PROSPECTjpsjournal1
The rivalry between prominent international actors for dominance over Central Asia's hydrocarbon
reserves and the ancient silk trade route, along with China's diplomatic endeavours in the area, has been
referred to as the "New Great Game." This research centres on the power struggle, considering
geopolitical, geostrategic, and geoeconomic variables. Topics including trade, political hegemony, oil
politics, and conventional and nontraditional security are all explored and explained by the researcher.
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Developmentof Image Enhancement and the Feature Extraction Techniques on Rural Fingerprint Images to Improve the Recognition and the Authentication Rate.
1. IOSR Journal of Computer Engineering (IOSR-JCE)
e-ISSN: 2278-0661, p- ISSN: 2278-8727Volume 15, Issue 1 (Sep. - Oct. 2013), PP 01-05
www.iosrjournals.org
www.iosrjournals.org 1 | Page
Developmentof Image Enhancement and the Feature Extraction
Techniques on Rural Fingerprint Images to Improve the
Recognition and the Authentication Rate.
Babasaheb V. Bhalerao, Ramesh R. Manza.
Department of Computer Science and Information Technology,
Dr. Babasaheb Ambedkar Marathwada University, Aurangabad (MS) India.
Abstract: Fingerprint recognition is one of the most popular and successful methods used for person
identification which takes advantage of the fact that the fingerprint has some unique characteristics called
minutiae which are points where a extracts the ridges and bifurcation from a fingerprint image. A critical step in
studying the statistics of fingerprint minutiae is to reliably extract minutiae from the fingerprint images.
However fingerprint images are rarely of perfect quality. Fingerprint image enhancement techniques are
employed prior to minutiae extraction to obtain a more reliable estimation of minutiae locations.
Fingerprint matching is often affected by the presence of intrinsically low quality fingerprints and various
distortions introduced during the acquisition process. In this paper we have used the rural fingerprints
database which is collected from IIIT Delhi research lab which consists of 1634 fingerprints images. Out of
which we have preprocess 600 sample preprocessing extracts the ridges and bifurcation from a fingerprint
image and tried to improve the quality of images. The Resultant images quality is verified by using different
quality measures.
Keywords: minutiae extraction, extracts the ridges and bifurcation, rural fingerprint authentication.
I. Introduction
Fingerprint matching is among the most widely used biometric technologies with a broad range of both
government and civilian applications such as a UIDAI, passport control, ATM/credit card, The key challenge in
fingerprint matching is getting a match decision between a pair of fingerprints from the same finger under
various within-class variations. Our implementation mainly noisy rural fingerprint images enhancement, image
segmentation, minutiae extraction.
Fingerprint recognition or fingerprint authentication refers to the automated method of verifying a
match between two human fingerprints. Fingerprints are one of many forms of biometrics used to identify an
individual and verify their identity. Because of their uniqueness and consistency over time, fingerprints have
been used for over a century.
The word “Biometrics” comes from the Greek language and is derived from the words “Biomeans life
and „metric‟ means to be measure, so biometrics is a field of science and technology used to be measure life
characteristics. Biometrics System uses physical and behavioral parameters for person identification. Biometric
data are unique for each individual person, even two identical twins. Basically we can use physical parameters
than behavioral because behavioral parameters are changed with age and environment whereas physical
parameters never changed during whole life. Fingerprint matching techniques are divided into three main types:
*Correlation based matching
* Minutiae based matching
* Pattern based matching.
Minutiae based matching is the most popular and most widely used technique for fingerprint matching. This
technique refers the analysis of some unique point’s exhibit on fingerprint called minutiae points. The detection
and representation of these points are also known as minutiae set. There are two basic minutiae points are
majorly used for matching in minutiae based technique, that is Ridge-end, which means the end of the ridges
and Bifurcation points, which means one single ridge divided into two ridges.
Figure 1.Ridges-end point, Bifurcation point
2. Developmentof Image Enhancement and the Feature Extraction Techniques on Rural Fingerprint
www.iosrjournals.org 2 | Page
II. Fingerprint Recognition:
Fingerprint recognition system can be used to analyze two fingerprint images one is original image and
another one is template image stored in the database. Fingerprint recognition is mainly divided in two sub-parts:
one is verification system and other is identification system. Fingerprint verification is used to verify the
authenticity of one person with one to one matching of the database, while fingerprint identification is used to
specify the person identification with one to n matching, fingerprint verification is rapid execution method than
fingerprint identification. Fingerprint identification is especially serviceable for criminal investigation cases.
MATLAB software provides the best image processing toolbox. Digital fingerprint images can analyze easily
using MATLAB. In this paper we present the result of implementation of algorithm on MATLAB.
III. Methodology
The complete algorithm is as follows: Input: Introduce fingerprint Image. Output: Matching score or total
number of both ridges-end and bifurcation points.
Figure2.Rural Fingerprint Original Images
Step1: Acquisition of fingerprint image. Step2: Convert image into binary form.
Step3: Apply thinning process on the binary image.
Step4: Find total numbers of ridges-end points and bifurcation points.
Step5: Match both minutiae points for fingerprint verification.
Figure 3.Flow
Pre-Processing:
Pre-processing is the process of alter a gray scale image to a black and white image. In MATLAB, a
value of one represents that the pixel is white and value of zero represents that the pixel is black. This
modification of gray scale image to binary image is executed by using threshold process to the image. When a
threshold process is applied to an image, each pixel values are analyzed to the input threshold. Those pixel
values which are smaller than the threshold value is place to zero and those pixel value which are greater than
the threshold value is place to one. At the end of this process each pixel values within the image are either zero
or one, and the image has been modifying to binary form. After this conversion the ridges in the fingerprint are
highlighted with black color while valleys are highlighted with white color.
Minutiae Extraction:
In fingerprint extraction have an accurate representation of the fingerprint image is critical to automatic
fingerprint identification systems, because most deployed commercial&non commercial large-scale systems are
dependent on feature-based matching Among all the fingerprint features, minutia point features with
corresponding orientation maps are unique enough to differenceamongst fingerprints robustly; the minutiae
feature representation reduces the complex fingerprint recognition problem to a point pattern matching problem.
In order to achieve high-accuracy minutiae with varied quality fingerprint images, segmentation algorithm needs
to separate foreground from noisy background which includes all ridge-valley regions and not the background.
Image Acquisition Pre-Processing
CalculationResult
Fingerpr
int
Image
Binary
Count
Total No
of
Ridges-
end
Points
and
Bifurcati
on
Points
Minutia
e Points
Matchin
g
3. Developmentof Image Enhancement and the Feature Extraction Techniques on Rural Fingerprint
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Image enhancement andFeature Extraction Techniques algorithm needs to keep the original ridge flow pattern
without altering the singularity, join broken ridges, clean artifacts between pseudo-parallel ridges, and not
introduce false information. Finally minutiae detection algorithm needs to locate efficiently and accurately the
minutiae points
Figure 4.Input Image after Bifurcations
Thinning:
After binarization, next leading pre-processing technique used for matching process is thinning. Image
thinning is the process ofdecrease thethickness of all ridges lines intosingle pixelwidth. Thinning process does
not convert the original x, y location and angle of direction of the minutiae points of the image, which assure the
true calculation of minutiae points. It is also known as Block Filtering. Ridges thinning are used to destruct the
extra pixel of ridges till the ridges are just one pixel broad this is done using MATLAB.
Figure 5Input images after thinning Minutiae
Input images after thinningMinutiae extraction:
Rural Fingerprint analysis using minutiae extraction process with the combination of several
techniques for image pre-processing and post-processing steps to improve the input image until it is suitable for
minutiae extraction. Preprocessing steps are crucial for further minutiae extraction. The Minutiae Extraction is
done by
Points Searching:
The proposed algorithm detects the Minutiae Points on the basis of Ridges are disconnected at arbitrary
point: Ridge-end Point and Ridges are associated with bifurcations: Bifurcation Point.
The classification of ridge-end or bifurcation points is done in MATLAB by creating matrix. If the
central pixel is one, has only one neighbor pixel that is ridge-end point. Whereas, if the central pixel is one, has
two neighbor pixel that is bifurcation point.
Minutiae Matching:
Image Acquisition
Fingerprint image.BMP = Input Image acquisition from reader.
Timage BMP = Template Image retrieve from database.
Computation of Value:
This step is a very important part of fingerprint matching. After the detection of minutiae points,
matching algorithm require to calculate total number of available points in the fingerprint image separately. To
perform this computation two counter variables are used to count both ridge-end and bifurcation points.
Minutiae extraction Bifurcations value
Table 1: Minutiae extraction Bifurcations value
Sr .No Name of Fingerprint Image Bifurcation
(Value)
1 BBrural fingerprint01_1bmp 522
2 BBrural fingerprint01_2bmp 699
3 BBrural fingerprint01_3bmp 578
4 BBrural fingerprint01_4bmp 701
5 BBrural fingerprint01_5bmp 380
6 BBrural fingerprint01_6bmp 488
7 BBrural fingerprint01_7bmp 623
8 BBrural fingerprint01_8bmp 690
9 BBrural fingerprint01_9bmp 362
4. Developmentof Image Enhancement and the Feature Extraction Techniques on Rural Fingerprint
www.iosrjournals.org 4 | Page
10 BBrural fingerprint01_10bmp 296
11 BBrural fingerprint2_1bmp 830
12 BBrural fingerprint2_2bmp 760
13 BBrural fingerprint2_3bmp 857
14 BBrural fingerprint2_4bmp 773
15 BBrural fingerprint2_5bmp 811
16 BBrural fingerprint2_6bmp 651
17 BBrural fingerprint2_7bmp 664
18 BBrural fingerprint2_8bmp 752
19 BBrural fingerprint2_9bmp 675
20 BBrural fingerprint2_10bmp 775
21 BBrural fingerprint3_1bmp 788
22 BBrural fingerprint3_2bmp 685
23 BBrural fingerprint3_3bmp 786
24 BBrural fingerprint3_4bmp 942
25 BBrural fingerprint3_5bmp 957
26 BBrural fingerprint3_6bmp 823
27 BBrural fingerprint3_7bmp 709
28 BBrural fingerprint3_8bmp 515
29 BBrural fingerprint3_9bmp 645
30 BBrural fingerprint3_10bmp 579
31 BBrural fingerprint4_1bmp 1224
32 BBrural fingerprint4_2bmp 488
33 BBrural fingerprint4_3bmp 794
34 BBrural fingerprint4_4bmp 745
35 BBrural fingerprint4_5bmp 507
36 BBrural fingerprint4_6bmp 690
37 BBrural fingerprint4_7bmp 696
38 BBrural fingerprint4_8bmp 420
39 BBrural fingerprint4_9bmp 672
40 BBrural fingerprint4_10bmp 594
Fig 6 Bifurcations valueGraph
Each minutiae point in the fingerprint image has a specific location. This location information of particular point
is significant to store for further matching of fingerprints. The location of every point in the digital image is
given by pixel position, so that it can be taken and stored separately for both ridge-end and bifurcation points.
Figure 7Minutiae point extracted in input images
IV. Conclusion:
In large scale deployment of fingerprint recognition systems, especially in rural fingerprints database,
there are some challenges involved. Along with the sensor noise and poor image quality, presence of scars and
5. Developmentof Image Enhancement and the Feature Extraction Techniques on Rural Fingerprint
www.iosrjournals.org 5 | Page
warts, and deteriorating ridge/minutiae patterns in fingerprints from rural population affect the data distribution.
Since there is no research that evaluates the performance of automatic fingerprint verification/identification in
rural fingerprints databases.We will studied the performance using standard fingerprint recognition systems and
fingerprint databases collected from the rural fingerprints databases, Indian population now a day’s it has been
work on unique identification where but when there is enhancement with such noisy fingerprints hence our
research work concentrated on same. In this paper we have perform minutiae extraction fingerprint images of
rural fingerprint image database. We have selected 600 images out of 1632. In this paper sample result of first
forty images out of six hundred given.Fingerprint image enhancement techniques are employed prior to
minutiae extraction to obtain a more reliable estimation of minutiae locations very much useful to enhance the
quality of rural fingerprint image database.
Acknowledgement:
We are very much thankful to Image Analysis and Biometrics (IAB) Lab at Indraprastha Institute of
Information Technology, IIIT Delhi for providing rural fingerprint database& Special thanks SAP DSR Phase-I
of Dept of Computer Science &IT, Dr. Babasaheb Ambedkar Marthwada University, and Aurangabad.
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