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.
Reduction of False Acceptance Rate Using Cross Validation for Fingerprint Rec...IJTET Journal
Abstract— In the field of biometric modality fingerprint is considered to be one of the most widely used method for individual identity. The fingerprint authentication is used in most application for security purpose. In the biometric systems, the input images are binarized and feature is extraction. The Minutiae matching in fingerprint identification is done by identifying the minutiae point of interest and their relationship. The validation testing in the proposed system using the method of K- fold cross validation by using two , a training set and test set of images to find the appropriate image that matches the input image ,increase the accuracy of recognition by reducing the false acceptance rate of the system.
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.
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.
Reduction of False Acceptance Rate Using Cross Validation for Fingerprint Rec...IJTET Journal
Abstract— In the field of biometric modality fingerprint is considered to be one of the most widely used method for individual identity. The fingerprint authentication is used in most application for security purpose. In the biometric systems, the input images are binarized and feature is extraction. The Minutiae matching in fingerprint identification is done by identifying the minutiae point of interest and their relationship. The validation testing in the proposed system using the method of K- fold cross validation by using two , a training set and test set of images to find the appropriate image that matches the input image ,increase the accuracy of recognition by reducing the false acceptance rate of the system.
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.
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.
bulk ieee projects in pondicherry,ieee projects in pondicherry,final year ieee projects in pondicherry
Nexgen Technology Address:
Nexgen Technology
No :66,4th cross,Venkata nagar,
Near SBI ATM,
Puducherry.
Email Id: praveen@nexgenproject.com.
www.nexgenproject.com
Mobile: 9751442511,9791938249
Telephone: 0413-2211159.
NEXGEN TECHNOLOGY as an efficient Software Training Center located at Pondicherry with IT Training on IEEE Projects in Android,IEEE IT B.Tech Student Projects, Android Projects Training with Placements Pondicherry, IEEE projects in pondicherry, final IEEE Projects in Pondicherry , MCA, BTech, BCA Projects in Pondicherry, Bulk IEEE PROJECTS IN Pondicherry.So far we have reached almost all engineering colleges located in Pondicherry and around 90km
Fingerprint Feature Extraction, Identification and Authentication: A Reviewpaperpublications3
Abstract: In the modern computerized world, due to high demand on fingerprint identification system, a lot of challenges keep arising in each phase of system, which include fingerprint image enhancement, feature extraction, features matching and fingerprint classification. Applications such as online banking and online shopping use techniques that depend on personal identification numbers, keys, or passwords. But there is the risk of data being forgotten, lost, or even stolen. One of the solutions to it may be biometric authentication methods which provide a unique way to identify, recognize and authenticate people. Fingerprints being the oldest methods of biometric authentication, are being explored at large. The main focus of the paper is to review fingerprint feature extraction, identification and authentication in different image/pattern based and minutiae-based fingerprints.
A Deep Neural Framework for Continuous Sign Language Recognition by Iterative...ijtsrd
Sign Language SL is a medium of communication for physically disabled people. It is a gesture based language for communication of dumb and deaf people. These people communicate by using different actions of hands, where each different action means something. Sign language is the only way of conversation for deaf and dumb people. It is very difficult to understand this language for the common people. Hence sign language recognition has become an important task. There is a necessity for a translator to communicate with the world. Real time translator for sign language provides a medium to communicate with others. Previous methods employs sensor gloves, hat mounted cameras, armband etc. which has wearing difficulties and have noisy behaviour. To alleviate this problem, a real time gesture recognition system using Deep Learning DL is proposed. It enables to achieve improvements on the gesture recognition performance. Jeni Moni | Anju J Prakash ""A Deep Neural Framework for Continuous Sign Language Recognition by Iterative Training: Survey"" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-4 | Issue-2 , February 2020,
URL: https://www.ijtsrd.com/papers/ijtsrd30032.pdf
Paper Url : https://www.ijtsrd.com/engineering/computer-engineering/30032/a-deep-neural-framework-for-continuous-sign-language-recognition-by-iterative-training-survey/jeni-moni
Hand and wrist localization approach: sign language recognition Sana Fakhfakh
This paper proposes a new hand detection and wrist localization method which presents an important step in the hand gesture recognizing process. The wrist localization step has not been given much attention and the existing works are limited and include many conditions. Our proposed approach was evaluated on a public dataset whose obtained results underscore its performance. We highlight through a comparative study with existing work, the superiority of our approach and the importance of the wrist localization step. We also propose to benefit from our proposed method which can be applied in the sign language recognition domain, and more precisely in the Arabic digit sign language recognition.
Automatic Isolated word sign language recognitionSana Fakhfakh
This paper suggests a new system to help the
deaf and the hearing-impaired community improve their
connection with the hearing world and communicate
freely. The most important thing in this system is
how to help the users be free and finally have a more
natural way of communication. For this reason, we
present a new process based on two levels: a static-level
aiming to extract the most head/hands key points and
a dynamic-level with the objective of accumulating the
key-point trajectory matrix. Also our proposed approach
takes into account the signer-independence constraint.
A SIGNUM database is applied in the classification
stage and our system performances have improved with
a 94.3% recognition rate. Furthermore, a reduction
in time processing is obtained when the removing of
redundant frame step is applied. The obtained results
prove the superiority of our system compared to the
state-of- the-art methods in terms of recognition rate and
execution time.
Detection and rectification of distorted fingerprintsCloudTechnologies
We are the company providing Complete Solution for all Academic Final Year/Semester Student Projects. Our projects are
suitable for B.E (CSE,IT,ECE,EEE), B.Tech (CSE,IT,ECE,EEE),M.Tech (CSE,IT,ECE,EEE) B.sc (IT & CSE), M.sc (IT & CSE),
MCA, and many more..... We are specialized on Java,Dot Net ,PHP & Andirod technologies. Each Project listed comes with
the following deliverable: 1. Project Abstract 2. Complete functional code 3. Complete Project report with diagrams 4.
Database 5. Screen-shots 6. Video File
SERVICE AT CLOUDTECHNOLOGIES
IEEE, WEB, WINDOWS PROJECTS ON DOT NET, JAVA& ANDROID TECHNOLOGIES,EMBEDDED SYSTEMS,MAT LAB,VLSI DESIGN.
ME, M-TECH PAPER PUBLISHING
COLLEGE TRAINING
Thanks&Regards
cloudtechnologies
# 304, Siri Towers,Behind Prime Hospitals
Maitrivanam, Ameerpet.
Contact:-8121953811,8522991105.040-65511811
cloudtechnologiesprojects@gmail.com
http://cloudstechnologies.in/
Study of Local Binary Pattern for Partial Fingerprint IdentificationIJMER
Fingerprints are usually used in recognition of a person's identity because of its uniqueness,
stability. Today also the matching of incomplete or partial fingerprints remains challenge. The current
technology is somewhat mature for matching ten prints, but matching of partial fingerprints still needs
a lot of improvement. Automatic fingerprint identification techniques have been successfully adapted to
both civilian and forensic applications. But this Fingerprint identification system suffers from the
problem of handling incomplete prints and discards any partial fingerprints obtained. Level 2 features
are very efficient if the quality of achievement decreases the number of level 2 features will not be
enough for establishing high accuracy in identification. In such cases pores (level 3 features) can be
used for partial fingerprint matching with the help of suitable technique local binary pattern features.
Local binary pattern feature is used to match the pore against with full fingerprints. The first step
involves extracting the pores from the partial image. These pores act as anchor points and sub window
(32*32) is formed surrounding the pores. Then rotation invariant LBP histograms are obtained from
the surrounding window. Finally chi-square formula is used to calculate the minimum distance between
two histograms to find best matching score
This presentation describes what could be the good features, and the methods to verify a person from his hand. This uses
"Raul Sanchez-Reillo, C. Sanchez-Avila, A. Gonzalez-Marcos, Biometric identification through hand geometry measurements, IEEE Transactions on PAMI 22 (2000)" as the base.
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.
novel method of identifying fingerprint using minutiae matching in biometric ...INFOGAIN PUBLICATION
Fingerprint is one of the best apparatus to identify human because of its uniqueness, details information, hard to change and long-term indicators of human identity where there are several biometric feature that can be recycled to endorse the individuality. Identification of fingerprint is very important in forensic science, trace any part of human, collection of crime part and proof from a crime. This paper presents a new method of identifying fingerprint in biometrics security system. Fingerprint is one of the best example in biometric security because it can identify personal information and it is much secure than any other biometric identification system. The experimental result exhibits the performance of the proposed method.
Biometrics was developed with the aim of improving the overall security level in all society contexts. A biometric system describes a set of techniques to analyze certain individual's biometric features, store and then using those patterns to identify or verify the identity of a person. The palmprint contains not only principal curves and wrinkles but also rich texture and miniscule points, so the palmprint identification is able to achieve a high accuracy because of available rich information in palmprint. Various palmprint identification methods, such as coding based methods and principal curve methods have been proposed in past decades. In addition to these methods, subspace based methods can also perform well for palmprint identification. Combining the left and right palmprint images to perform multibiometrics is easy to implement and can obtain better results.
Multimodal biometrics can provide higher identification accuracy than single or unimodal biometrics, so it is more suitable for some real-world personal identification applications that need high-standard security. A onetime password is included for higher security and accuracy.
One time passwords generally expire after using once. They are generated for using it within a certain time period after which it is useless. These passwords are set as a secondary security measure for the primary palmprint recognition.
Detecting and Improving Distorted Fingerprints using rectification techniques.sandipan paul
In this detection and improving distorted fingerprint using rectification techniques like SVM, PCA classifier etc.
In this ppt a distorted fingerprint is taken and improve that distorted fingerprint into normal one.
Developmentof Image Enhancement and the Feature Extraction Techniques on Rura...IOSR Journals
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.
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.
bulk ieee projects in pondicherry,ieee projects in pondicherry,final year ieee projects in pondicherry
Nexgen Technology Address:
Nexgen Technology
No :66,4th cross,Venkata nagar,
Near SBI ATM,
Puducherry.
Email Id: praveen@nexgenproject.com.
www.nexgenproject.com
Mobile: 9751442511,9791938249
Telephone: 0413-2211159.
NEXGEN TECHNOLOGY as an efficient Software Training Center located at Pondicherry with IT Training on IEEE Projects in Android,IEEE IT B.Tech Student Projects, Android Projects Training with Placements Pondicherry, IEEE projects in pondicherry, final IEEE Projects in Pondicherry , MCA, BTech, BCA Projects in Pondicherry, Bulk IEEE PROJECTS IN Pondicherry.So far we have reached almost all engineering colleges located in Pondicherry and around 90km
Fingerprint Feature Extraction, Identification and Authentication: A Reviewpaperpublications3
Abstract: In the modern computerized world, due to high demand on fingerprint identification system, a lot of challenges keep arising in each phase of system, which include fingerprint image enhancement, feature extraction, features matching and fingerprint classification. Applications such as online banking and online shopping use techniques that depend on personal identification numbers, keys, or passwords. But there is the risk of data being forgotten, lost, or even stolen. One of the solutions to it may be biometric authentication methods which provide a unique way to identify, recognize and authenticate people. Fingerprints being the oldest methods of biometric authentication, are being explored at large. The main focus of the paper is to review fingerprint feature extraction, identification and authentication in different image/pattern based and minutiae-based fingerprints.
A Deep Neural Framework for Continuous Sign Language Recognition by Iterative...ijtsrd
Sign Language SL is a medium of communication for physically disabled people. It is a gesture based language for communication of dumb and deaf people. These people communicate by using different actions of hands, where each different action means something. Sign language is the only way of conversation for deaf and dumb people. It is very difficult to understand this language for the common people. Hence sign language recognition has become an important task. There is a necessity for a translator to communicate with the world. Real time translator for sign language provides a medium to communicate with others. Previous methods employs sensor gloves, hat mounted cameras, armband etc. which has wearing difficulties and have noisy behaviour. To alleviate this problem, a real time gesture recognition system using Deep Learning DL is proposed. It enables to achieve improvements on the gesture recognition performance. Jeni Moni | Anju J Prakash ""A Deep Neural Framework for Continuous Sign Language Recognition by Iterative Training: Survey"" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-4 | Issue-2 , February 2020,
URL: https://www.ijtsrd.com/papers/ijtsrd30032.pdf
Paper Url : https://www.ijtsrd.com/engineering/computer-engineering/30032/a-deep-neural-framework-for-continuous-sign-language-recognition-by-iterative-training-survey/jeni-moni
Hand and wrist localization approach: sign language recognition Sana Fakhfakh
This paper proposes a new hand detection and wrist localization method which presents an important step in the hand gesture recognizing process. The wrist localization step has not been given much attention and the existing works are limited and include many conditions. Our proposed approach was evaluated on a public dataset whose obtained results underscore its performance. We highlight through a comparative study with existing work, the superiority of our approach and the importance of the wrist localization step. We also propose to benefit from our proposed method which can be applied in the sign language recognition domain, and more precisely in the Arabic digit sign language recognition.
Automatic Isolated word sign language recognitionSana Fakhfakh
This paper suggests a new system to help the
deaf and the hearing-impaired community improve their
connection with the hearing world and communicate
freely. The most important thing in this system is
how to help the users be free and finally have a more
natural way of communication. For this reason, we
present a new process based on two levels: a static-level
aiming to extract the most head/hands key points and
a dynamic-level with the objective of accumulating the
key-point trajectory matrix. Also our proposed approach
takes into account the signer-independence constraint.
A SIGNUM database is applied in the classification
stage and our system performances have improved with
a 94.3% recognition rate. Furthermore, a reduction
in time processing is obtained when the removing of
redundant frame step is applied. The obtained results
prove the superiority of our system compared to the
state-of- the-art methods in terms of recognition rate and
execution time.
Detection and rectification of distorted fingerprintsCloudTechnologies
We are the company providing Complete Solution for all Academic Final Year/Semester Student Projects. Our projects are
suitable for B.E (CSE,IT,ECE,EEE), B.Tech (CSE,IT,ECE,EEE),M.Tech (CSE,IT,ECE,EEE) B.sc (IT & CSE), M.sc (IT & CSE),
MCA, and many more..... We are specialized on Java,Dot Net ,PHP & Andirod technologies. Each Project listed comes with
the following deliverable: 1. Project Abstract 2. Complete functional code 3. Complete Project report with diagrams 4.
Database 5. Screen-shots 6. Video File
SERVICE AT CLOUDTECHNOLOGIES
IEEE, WEB, WINDOWS PROJECTS ON DOT NET, JAVA& ANDROID TECHNOLOGIES,EMBEDDED SYSTEMS,MAT LAB,VLSI DESIGN.
ME, M-TECH PAPER PUBLISHING
COLLEGE TRAINING
Thanks&Regards
cloudtechnologies
# 304, Siri Towers,Behind Prime Hospitals
Maitrivanam, Ameerpet.
Contact:-8121953811,8522991105.040-65511811
cloudtechnologiesprojects@gmail.com
http://cloudstechnologies.in/
Study of Local Binary Pattern for Partial Fingerprint IdentificationIJMER
Fingerprints are usually used in recognition of a person's identity because of its uniqueness,
stability. Today also the matching of incomplete or partial fingerprints remains challenge. The current
technology is somewhat mature for matching ten prints, but matching of partial fingerprints still needs
a lot of improvement. Automatic fingerprint identification techniques have been successfully adapted to
both civilian and forensic applications. But this Fingerprint identification system suffers from the
problem of handling incomplete prints and discards any partial fingerprints obtained. Level 2 features
are very efficient if the quality of achievement decreases the number of level 2 features will not be
enough for establishing high accuracy in identification. In such cases pores (level 3 features) can be
used for partial fingerprint matching with the help of suitable technique local binary pattern features.
Local binary pattern feature is used to match the pore against with full fingerprints. The first step
involves extracting the pores from the partial image. These pores act as anchor points and sub window
(32*32) is formed surrounding the pores. Then rotation invariant LBP histograms are obtained from
the surrounding window. Finally chi-square formula is used to calculate the minimum distance between
two histograms to find best matching score
This presentation describes what could be the good features, and the methods to verify a person from his hand. This uses
"Raul Sanchez-Reillo, C. Sanchez-Avila, A. Gonzalez-Marcos, Biometric identification through hand geometry measurements, IEEE Transactions on PAMI 22 (2000)" as the base.
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.
novel method of identifying fingerprint using minutiae matching in biometric ...INFOGAIN PUBLICATION
Fingerprint is one of the best apparatus to identify human because of its uniqueness, details information, hard to change and long-term indicators of human identity where there are several biometric feature that can be recycled to endorse the individuality. Identification of fingerprint is very important in forensic science, trace any part of human, collection of crime part and proof from a crime. This paper presents a new method of identifying fingerprint in biometrics security system. Fingerprint is one of the best example in biometric security because it can identify personal information and it is much secure than any other biometric identification system. The experimental result exhibits the performance of the proposed method.
Biometrics was developed with the aim of improving the overall security level in all society contexts. A biometric system describes a set of techniques to analyze certain individual's biometric features, store and then using those patterns to identify or verify the identity of a person. The palmprint contains not only principal curves and wrinkles but also rich texture and miniscule points, so the palmprint identification is able to achieve a high accuracy because of available rich information in palmprint. Various palmprint identification methods, such as coding based methods and principal curve methods have been proposed in past decades. In addition to these methods, subspace based methods can also perform well for palmprint identification. Combining the left and right palmprint images to perform multibiometrics is easy to implement and can obtain better results.
Multimodal biometrics can provide higher identification accuracy than single or unimodal biometrics, so it is more suitable for some real-world personal identification applications that need high-standard security. A onetime password is included for higher security and accuracy.
One time passwords generally expire after using once. They are generated for using it within a certain time period after which it is useless. These passwords are set as a secondary security measure for the primary palmprint recognition.
Detecting and Improving Distorted Fingerprints using rectification techniques.sandipan paul
In this detection and improving distorted fingerprint using rectification techniques like SVM, PCA classifier etc.
In this ppt a distorted fingerprint is taken and improve that distorted fingerprint into normal one.
Developmentof Image Enhancement and the Feature Extraction Techniques on Rura...IOSR Journals
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.
COMPARATIVE ANALYSIS OF MINUTIAE BASED FINGERPRINT MATCHING ALGORITHMSijcsit
Biometric matching involves finding similarity between fingerprint images.The accuracy and speed of the
matching algorithmdetermines its effectives. This researchaims at comparing two types of matching
algorithms namely(a) matching using global orientation features and (b) matching using minutia triangulation.The comparison is done using accuracy, time and number of similar features. The experiment is conducted on a datasets of 100 candidates using four (4) fingerprints from each candidate. The data is sampled from a mass registration conducted by a reputable organization in Kenya.Theresearch reveals that fingerprint matching based on algorithm (b) performs better in speed with an average of 38.32 milliseconds
as compared to matching based on algorithm (a) with an average of 563.76 milliseconds. On accuracy,algorithm(a) performs better with an average accuracy of 0.142433 as compared to algorithm (b) with an average accuracy score of 0.004202.
Highly Secured Bio-Metric Authentication Model with Palm Print IdentificationIJERA Editor
For securing personal identifications and highly secure identification problems, biometric technologies will
provide higher security with improved accuracy. This has become an emerging technology in recent years due to
the transaction frauds, security breaches and personal identification etc. The beauty of biometric technology is it
provides a unique code for each person and it can’t be copied or forged by others. To overcome the draw backs
of finger print identification systems, here in this paper we proposed a palm print based personal identification
system, which is a most promising and emerging research area in biometric identification systems due to its
uniqueness, scalability, faster execution speed and large area for extracting the features. It provides higher
security over finger print biometric systems with its rich features like wrinkles, continuous ridges, principal
lines, minutiae points, and singular points. The main aim of proposed palm print identification system is to
implement a system with higher accuracy and increased speed in identifying the palm prints of several users.
Here, in this we presented a highly secured palm print identification system with extraction of region of interest
(ROI) with morphological operation there by applying un-decimated bi-orthogonal wavelet (UDBW) transform
to extract the low level features of registered palm prints to calculate its feature vectors (FV) then after the
comparison is done by measuring the distance between registered palm feature vector and testing palm print
feature vector. Simulation results show that the proposed biometric identification system provides more
accuracy and reliable recognition rate
A Fast and Accurate Palmprint Identification System based on Consistency Orie...IJTET Journal
Abstract — A palmprint identification system is a relatively most promising physiological biometric approach to identify the person. The numbers of palmprint recognition based biometric system have been successfully applied for real world access to control applications. A typical palmprint identification system identifies a query palmprint and matching it with the template stored in the database and comparing the similarity score with a pre-defined threshold. The Consistency Orientation Pattern (COP) hashing method is implemented in this work to enforce the fast search and to obtain the accurate result. Orientation pattern (OP) is defined as a collection of orientation features at arbitrary positions. The principal palm line is a kind of evident and stable features in palmprint images, and the orientation features in this region are expected to be more consistent than others. Using the orientation and response features extracted by steerable filter and gives an analysis on the consistency of orientation features, and then introduces a method to construct COP using the consistent features. Those features can be used as the indexes to the target template. Because the COP is very stable across the samples of the same subject, the COP hashing method can find the target template quickly. This method can lead to early termination of the searching process.
An Efficient Fingerprint Identification using Neural Network and BAT Algorithm IJECEIAES
The uniqueness, firmness, public recognition, and its minimum risk of intrusion made fingerprint is an expansively used personal authentication metrics. Fingerprint technology is a biometric technique used to distinguish persons based on their physical traits. Fingerprint based authentication schemes are becoming increasingly common and usage of these in fingerprint security schemes, made an objective to the attackers. The repute of the fingerprint image controls the sturdiness of a fingerprint authentication system. We intend for an effective method for fingerprint classification with the help of soft computing methods. The proposed classification scheme is classified into three phases. The first phase is preprocessing in which the fingerprint images are enhanced by employing median filters. After noise removal histogram equalization is achieved for augmenting the images. The second stage is the feature Extraction phase in which numerous image features such as Area, SURF, holo entropy, and SIFT features are extracted. The final phase is classification using hybrid Neural for classification of fingerprint as fake or original. The neural network is unified with BAT algorithm for optimizing the weight factor.
Fingerprint Recognition Using Minutiae Based and Discrete Wavelet TransformAM Publications
Fingerprint recognition is one of the methods used in biometric system. Most of the biometric systems which are used for human identification or person’s identification. In this paper we are discussing minutiae matching and discrete wavelet transform and comparison of these two in fingerprint recognition. In this paper, firstly it uses fingerprint identification and performance in terms of equal error rate and then by calculating using discrete wavelet transform. The main aim of this paper is to create performing and accurate program for fingerprint identification.
Analysis of Image Fusion Techniques for fingerprint Palmprint Multimodal Biom...IJERA Editor
The multimodal Biometric System using multiple sources of information has been widely recognized. However computational models for multimodal biometrics recognition have only recently received attention. In this paper the fingerprint and palmprint images are chosen and fused together using image fusion methods. The biometric features are subjected to modality extraction. Different fusion methods like average fusion, minimum fusion, maximum fusion, discrete wavelet transform fusion and stationary wavelet transformfusion are implemented for the fusion of extracting modalities. The best fused template is analyzed by applying various fusion metrics. Here the DWT fused image provided better results.
Biometric identification with improved efficiency using sift algorithmIJARIIT
Osseo-integrated dental implants have been widely used for the rehabilitation of tooth loss. Although dental implants
are considered an available treatment in the paradigm shift from traditional dental therapies, such as fixed dental bridges and
removable dentures, the fundamental problems must be overcome prior to their clinical use in young patients who are still
undergoing jawbone growth. A bio-engineered functional bio-hybrid implant that is combined with adult-derived periodontal
tissue and attached with bone tissue can act as a substitute for cementum. This bio-hybrid implant was successfully engrafted
and it restored physiological function, including bone remodelling, regeneration and appropriate responsiveness to noxious
stimuli. Thus, this article reviews the functional bio-hybrid implant’s potential for clinical use as a next-generation dental
implant using adult-derived tissues.
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.
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.
International Journal of Computational Engineering Research(IJCER)ijceronline
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Ijaems apr-2016-1 Multibiometric Authentication System Processed by the Use o...INFOGAIN PUBLICATION
The present day authentication system is mostly uni-model i.e having only single authentication method which can be either finger print, iris , palm veins ,etc. Thus these models have to contend with a variety of problems such as absurd or unusual data, non-versatility; un authorized attempts, and huge amount of error rates. Some of these limitations can be reduced or stopped by the use of multimodal biometric systems that integrate the evidence presented by several sources of information. This paper converses a multi biometric based authentication system based on Fusion algorithm using a key. Our work mainly focuses on the fusion algorithm, i.e fusion of finger and palm print out of which the greatest features from the above two traits are taken into account. With minimum possible features the fusion of the both the traits is carried out. Then some key is generated for multi biometric authentication. By processing the test image of a person, the identity of the person is displayed with his/her own image. By the fusion algorithm, it is found that it has less computation time compared to the existing algorithms. By matching results, we validate and authenticate the particular individual.
A Review on Feature Extraction Techniques and General Approach for Face Recog...Editor IJCATR
In recent time, alongwith the advances and new inventions in science and technology, fraud people and identity thieves are
also becoming smarter by finding new ways to fool the authorization and authentication process. So, there is a strong need of efficient
face recognition process or computer systems capable of recognizing faces of authenticated persons. One way to make face recognition
efficient is by extracting features of faces. Several feature extraction techniques are available such as template based, appearancebased,
geometry based, color segmentation based, etc. This paper presents an overview of various feature extraction techniques
followed in different reasearches for face recognition in the field of digital image processing and gives an approach for using these
feature extraction techniques for efficient face recognition
Fingerprints are imprints formed by friction
ridges of the skin and thumbs. They have long been used for
identification because of their immutability and individuality.
Immutability refers to the permanent and unchanging character
of the pattern on each finger. Individuality refers to the
uniqueness of ridge details across individuals; the probability
that two fingerprints are alike is about 1 in 1.9x1015. In despite of
this improvement which is adopted by the Federal Bureau of
Investigation (FBI), the fact still is “The larger the fingerprint
files became, the harder it was to identify somebody from their
fingerprints alone. Moreover, the fingerprint requires one of the
largest data templates in the biometric field”. The finger data
template can range anywhere from several hundred bytes to over
1,000 bytes depending upon the level of security that is required
and the method that is used to scan one's fingerprint. For these
reasons this work is motivated to present another way to tackle
the problem that is relies on the properties of Vector
Quantization coding algorithm.
Enhanced Latent Fingerprint Segmentation through Dictionary Based ApproachEditor IJMTER
The accuracy of latent finger print matching compared to roll and plain finger print
matching is significantly lower due to background noise, poor ridge quality and overlapping
structured noise in latent images. In this paper the proposed algorithm is dictionary-based approach
for automatic segmentation and enhancement towards the goal of achieving “lights out” latent
identifications system. Total variation decomposition model with L1 fidelity regularization in latent
finger print image remove background noise. A coarse to fine strategy is used to improve robustness
and accuracy. It improves the computational efficiency of the algorithm.
DevOps and Testing slides at DASA ConnectKari Kakkonen
My and Rik Marselis slides at 30.5.2024 DASA Connect conference. We discuss about what is testing, then what is agile testing and finally what is Testing in DevOps. Finally we had lovely workshop with the participants trying to find out different ways to think about quality and testing in different parts of the DevOps infinity loop.
The Art of the Pitch: WordPress Relationships and SalesLaura Byrne
Clients don’t know what they don’t know. What web solutions are right for them? How does WordPress come into the picture? How do you make sure you understand scope and timeline? What do you do if sometime changes?
All these questions and more will be explored as we talk about matching clients’ needs with what your agency offers without pulling teeth or pulling your hair out. Practical tips, and strategies for successful relationship building that leads to closing the deal.
Connector Corner: Automate dynamic content and events by pushing a buttonDianaGray10
Here is something new! In our next Connector Corner webinar, we will demonstrate how you can use a single workflow to:
Create a campaign using Mailchimp with merge tags/fields
Send an interactive Slack channel message (using buttons)
Have the message received by managers and peers along with a test email for review
But there’s more:
In a second workflow supporting the same use case, you’ll see:
Your campaign sent to target colleagues for approval
If the “Approve” button is clicked, a Jira/Zendesk ticket is created for the marketing design team
But—if the “Reject” button is pushed, colleagues will be alerted via Slack message
Join us to learn more about this new, human-in-the-loop capability, brought to you by Integration Service connectors.
And...
Speakers:
Akshay Agnihotri, Product Manager
Charlie Greenberg, Host
"Impact of front-end architecture on development cost", Viktor TurskyiFwdays
I have heard many times that architecture is not important for the front-end. Also, many times I have seen how developers implement features on the front-end just following the standard rules for a framework and think that this is enough to successfully launch the project, and then the project fails. How to prevent this and what approach to choose? I have launched dozens of complex projects and during the talk we will analyze which approaches have worked for me and which have not.
Epistemic Interaction - tuning interfaces to provide information for AI supportAlan Dix
Paper presented at SYNERGY workshop at AVI 2024, Genoa, Italy. 3rd June 2024
https://alandix.com/academic/papers/synergy2024-epistemic/
As machine learning integrates deeper into human-computer interactions, the concept of epistemic interaction emerges, aiming to refine these interactions to enhance system adaptability. This approach encourages minor, intentional adjustments in user behaviour to enrich the data available for system learning. This paper introduces epistemic interaction within the context of human-system communication, illustrating how deliberate interaction design can improve system understanding and adaptation. Through concrete examples, we demonstrate the potential of epistemic interaction to significantly advance human-computer interaction by leveraging intuitive human communication strategies to inform system design and functionality, offering a novel pathway for enriching user-system engagements.
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...DanBrown980551
Do you want to learn how to model and simulate an electrical network from scratch in under an hour?
Then welcome to this PowSyBl workshop, hosted by Rte, the French Transmission System Operator (TSO)!
During the webinar, you will discover the PowSyBl ecosystem as well as handle and study an electrical network through an interactive Python notebook.
PowSyBl is an open source project hosted by LF Energy, which offers a comprehensive set of features for electrical grid modelling and simulation. Among other advanced features, PowSyBl provides:
- A fully editable and extendable library for grid component modelling;
- Visualization tools to display your network;
- Grid simulation tools, such as power flows, security analyses (with or without remedial actions) and sensitivity analyses;
The framework is mostly written in Java, with a Python binding so that Python developers can access PowSyBl functionalities as well.
What you will learn during the webinar:
- For beginners: discover PowSyBl's functionalities through a quick general presentation and the notebook, without needing any expert coding skills;
- For advanced developers: master the skills to efficiently apply PowSyBl functionalities to your real-world scenarios.
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Topics covered:
UI automation Introduction,
UI automation Sample
Desktop automation flow
Pradeep Chinnala, Senior Consultant Automation Developer @WonderBotz and UiPath MVP
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using Deplo...James Anderson
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The modern software delivery process (or the CI/CD process) includes many tools, distributed teams, open-source code, and cloud platforms. Constant focus on speed to release software to market, along with the traditional slow and manual security checks has caused gaps in continuous security as an important piece in the software supply chain. Today organizations feel more susceptible to external and internal cyber threats due to the vast attack surface in their applications supply chain and the lack of end-to-end governance and risk management.
The software team must secure its software delivery process to avoid vulnerability and security breaches. This needs to be achieved with existing tool chains and without extensive rework of the delivery processes. This talk will present strategies and techniques for providing visibility into the true risk of the existing vulnerabilities, preventing the introduction of security issues in the software, resolving vulnerabilities in production environments quickly, and capturing the deployment bill of materials (DBOM).
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Bob Boule
Robert Boule is a technology enthusiast with PASSION for technology and making things work along with a knack for helping others understand how things work. He comes with around 20 years of solution engineering experience in application security, software continuous delivery, and SaaS platforms. He is known for his dynamic presentations in CI/CD and application security integrated in software delivery lifecycle.
Gopinath Rebala
Gopinath Rebala is the CTO of OpsMx, where he has overall responsibility for the machine learning and data processing architectures for Secure Software Delivery. Gopi also has a strong connection with our customers, leading design and architecture for strategic implementations. Gopi is a frequent speaker and well-known leader in continuous delivery and integrating security into software delivery.
Let's dive deeper into the world of ODC! Ricardo Alves (OutSystems) will join us to tell all about the new Data Fabric. After that, Sezen de Bruijn (OutSystems) will get into the details on how to best design a sturdy architecture within ODC.
Smart TV Buyer Insights Survey 2024 by 91mobiles.pdf91mobiles
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Transcript: Selling digital books in 2024: Insights from industry leaders - T...BookNet Canada
The publishing industry has been selling digital audiobooks and ebooks for over a decade and has found its groove. What’s changed? What has stayed the same? Where do we go from here? Join a group of leading sales peers from across the industry for a conversation about the lessons learned since the popularization of digital books, best practices, digital book supply chain management, and more.
Link to video recording: https://bnctechforum.ca/sessions/selling-digital-books-in-2024-insights-from-industry-leaders/
Presented by BookNet Canada on May 28, 2024, with support from the Department of Canadian Heritage.
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II. Types of fingerprint:
FIGURE: 1 FIGURE: 2
FIGURE: 3 FIGURE: 4
FIGURE: 5 FIGURE: 6
FIGURE: 7
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III. LITERATURE REVIEW
There are three categories of fingerprint matching techniques:
a. Correlation-based technique.
b. Minutiae-based technique.
c. Pattern based technique.
a) Correlation-based technique: Two fingerprint images are super overlapped and the correlation
between corresponding pixels is computed for different alignments (e.g. various displacements and
rotations).
b) Minutiae-based technique: This is the most popular and widely used technique. Here the two
basic steps are 1. Minutiae Extraction. 2. Minutiae matching. Minutiae’s are removed from the two
fingerprints and stored as sets of points in the two- dimensional plane. Minutiae-based matching
essentially consists of finding the alignment between the template and the input minutiae sets the
result in the maximum number of minutiae pairings.
c) Pattern-based technique: Pattern based algorithms compare the basic fingerprint patterns (arch,
whorl, and loop) between a previously stored template and a candidate fingerprint. This requires that
the images be aligned in the same orientation. To do this, the algorithm finds a central point in the
fingerprint image and centers on that. In a pattern-based algorithm, the template contains the type,
size, and orientation of patterns within the aligned fingerprint image. The candidate fingerprint
image is graphically compared with the template to determine the degree to which they match.
Most of the automatic fingerprint recognition systems today depend on minutiae-based
matching because minutiae are easy to store and take much lesser space than correlation based
technique but are more time consuming. Sangram Bana nad Dr. Davinder Kaur [4] proposed
minutiae extraction and minutiae matching using segmentation and thinning for fingerprint
recognition. Sarnali Basak, Md. Imdadul Islam, M. R. Amin [5] proposed a new method of virtual
core point detection based on the change in gradient of maxima and minima points and the region of
interest is obtained for further processing. Ashish Mishra and Dr. Madhu Shandilya[6] introduced
gradient based technique and optimized neighborhood averaging to generate a smoother orientation
field for detecting core point. Dr. H.B.Kekre, Dr.Tanuja Sarode and Rekha Vig[7] proposed image
based method for extraction of feature vectors using sectorization of cepstrum. K.B.Raja, Shashi
Kumar D R, R K chhotaray, Sabyasachi Pattanaik[8] proposed a DWT based recognition using Non-
Minutiae (DWTFR) algorithm. Vipul Awasthi, Vanchha Awasthi and Krishna Kumar Tiwari[9]
proposed a technique of minutiae extraction with a combination of several pre-processing and post-
processing and also termination and bifurcation are used.
The correlation-based fingerprint verification that is proposed in this section, it is compared
to the traditional minutiae-based methods:
The advantages of the correlation based method over minutiae are:
The method uses the much richer gray-level information of the fingerprint image instead of
only positions of minutiae.
The method is also accomplished of dealing with fingerprints of bad image quality from
which no minutiae can be extracted reliably.
False and missed minutiae do not decrease the matching performance.
Unlike the minutiae templates, the template locations are already paired, which results in
much simpler matching methods. When registering minutiae sets, it is not known in advance
which minutiae from both sets should correspond.
The first decision stage only classifies relative template positions. This method tolerates non-
uniform local shape distortions in the fingerprint, unlike the minutiae templates for which the
optimal global transform is searched.
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The disadvantages of the correlation-based fingerprint verification method are:
Template matching requires high computational power, which makes the method less applicable
for real time applications.
The method is at the instant not capable of dealing with rotations of more than about 10
degrees. This is caused by the actuality that for larger rotations, the templates don't match
well anymore, causing incorrect positions to be found. A solution to this problem is rotating the
templates and then performing the matching again. However, this is a solution that requires a
lot of additional computational power.
Problems might come if the minutiae-based or coherence-based template selection methods are
used while 2 minutiae surroundings look like a lot. In this case, there is a probability that
template matching will and the incorrect template position, which degrades the matching
performance. Use of the correlation characteristic template selection will solve this problem.
IV. CHALLENGES WITH FINGERPRINT IDENTIFICATION
Some of the common challenges related to fingerprint technology are low quality or
corrupted input images, noise reduction, etc. The low quality or degraded images is the most
common problem. The degradation can be due to burns, cuts, dust particles, etc. The fingerprint
enhancement techniques not only enhance the low quality image but also remove the noise.
O’Gonnan and Nickerson [10] proposed the method contextual filtering for fingerprint
enhancement. Shlomo Greenberg [11] applied anisotrophic filter for fingerprint enhancement. Hong
et al. [12], reported fingerprint enhancement based on the estimated local ridge orientation and
frequency clarification of ridge and valley structures of input. Lin Hong [13] employed Gabor filter
in enhancing the image because gabor filters have both frequency selective and orientation selective
properties. D.Maio [14] used a Gaussian shape mask filter to filter selected section in every step.
Wang [15] proposed a method of Log-Gabor filter. Cavuso Glu [16] proposed a fast filtering method
based on reference mask of parabolic coefficients.
V. CONCLUSION
Fingerprint identification is one of the common and oldest forms of biometrics but the actual
truth is that still a lot of research is to be done due to its complexity and Intractability. The future
research work in this field is:
a. Secure biometric systems: The fingerprint has proved to be secure due to its unique and
unchanging behavior but there are various threats like attacks on communication, attack on
database like able to obtain a fingerprint from database or injecting a new fingerprint in
database, presenting fake fingerprint.
b. Better feature extraction: We need to improve the various extraction algorithms for feature
extraction and give accurate result and more features to be extracted in less time.
c. Better matching and alignment: The matching and alignment needs to be faster and accuracy
should be improved.
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pp. 17-18’, 1900.
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[4] Sangram Bana, Dr. Davinder Kaur , ‘Fingerprint Recognition using image segmentation’ , feb-
2011
[5] Basak, Md. Imdadul Islam, M. R. Amin, ‘Detection of a virtual core point a fingerprint: A new
approach’, May-2012
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mask’, June-2010.
[7] Dr. H.B.kehre, Dr. Tanuja Sarade, Rekha Vig, ‘Fingerprint identification using sectorized
cepstrum’, oct-2010.
[8] Shashi Kumar D R, K B Raja, R K Chhotaray, Sabyasachi Pattanaik, ‘DWT based fingerprint
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[10] L. O’Gonnan, J.V. Nickerson, ‘Matched filter design for fingerprint image enhancement, in
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September 3-8, IEEE Computer Society Press’
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evaluation,IEEE Trans. Pattern Anal. Mach. Intell. (1998) 777–789.’
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[14] D. Maio, D. Maltoni, ‘Direct Gray-scale Minutiae Detection in Fingerprints,’ IEEE Trans.
Pattern Anal. Mach. Intell.19, pp.27-39, 1997.
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fingerprint image enhancement, Pattern Recognition Lett. 29 (2008) 301–308.’
[16] A. Çavuso lu, S. Görgüno lu, ‘A fast fingerprint image enhancement algorithm using a
parabolic mask, Comput. Electr. Eng. (2008) 250–256.’
[17] Dr. Mustafa Dhiaa Al-Hassani, Dr. Abdulkareem A. Kadhim and Dr. Venus W. Samawi,
“Fingerprint Identification Technique Based on Wavelet-Bands Selection Features (WBSF)”
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