This document proposes using a cuckoo search algorithm to optimize the process of fingerprint matching for biometric identification. It begins by introducing biometric recognition and some of its challenges with large and complex datasets. It then provides background on cuckoo search optimization and describes how it can be applied to optimize fingerprint matching. Specifically, it presents an algorithm that extracts sub-matrices of increasing dimension from a fingerprint image matrix and uses cuckoo search to match fingerprints by comparing the sub-matrices until an accurate match is found. The document simulates this algorithm and outlines the results, demonstrating how cuckoo search optimization may help address limitations of traditional techniques for complex biometric analysis.
MultiModal Identification System in Monozygotic TwinsCSCJournals
With the increase in the number of twin births in recent decades, there is a need to develop alternate approaches that can secure the biometric system. In this paper an effective fusion scheme is presented that combines information presented by multiple domain experts based on the rank-level fusion integration method. The developed multimodal biometric system possesses a number of unique qualities, starting from utilizing Fisher’s Linear Discriminant methods for face matching, Principal Component Analysis for fingerprint matching and Local binary pattern features for iris matching and fused the information for effective recognition and authentication The importance of considering these boundary conditions, such as twins, where the possibility of errors is maximum will lead us to design a more reliable and robust security system.The proposed approach is tested on a real database consisting of 50 pair of identical twin images and shows promising results compared to other techniques. The Receiver Operating Characteristics also shows that the proposed method is superior compared to other techniques under study.
Multimodal Biometrics at Feature Level Fusion using Texture FeaturesCSCJournals
In recent years, fusion of multiple biometric modalities for personal authentication has received considerable attention. This paper presents a feature level fusion algorithm based on texture features. The system combines fingerprint, face and off-line signature. Texture features are extracted from Curvelet transform. The Curvelet feature dimension is selected based on d-prime number. The increase in feature dimension is reduced by using template averaging, moment features and by Principal component analysis (PCA). The algorithm is tested on in-house multimodal database comprising of 3000 samples and Chimeric databases. Identification performance of the system is evaluated using SVM classifier. A maximum GAR of 97.15% is achieved with Curvelet-PCA features.
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.
Feature Level Fusion of Multibiometric Cryptosystem in Distributed SystemIJMER
ABSTRACT: Multibiometrics is the combination of one or more biometrics (e.g., Fingerprint, Iris, and Face). Researchers
are focusing on how to provide security to the system, the template which was generated from the biometric need to be
protected. The problems of unimodal biometrics are solved by multibiometrics. The main objective is to provide a security to
the biometric template by generating a secure sketch by making use of multibiometric cryptosystem and which is stored in a
database. Once the biometric template is stolen it becomes a serious issue for the security of the system and also for user
privacy. In the existing approach, feature level fusion is used to combine the features securely with well-known biometric
cryptosystems namely fuzzy vault and fuzzy commitment. The drawbacks of existing system include accuracy of the biometric
need to be improved and the noises in the biometrics also need to be reduced. The proposed work is to enhance the security
using multibiometric cryptosystem in distributed system applications like e-commerce transactions, e-banking and ATM.
Keywords: Biometric Cryptosystem, Error correcting code, Fingerprint, Iris, Multibiometrics, Unimodal biometrics.
A SURVEY ON DEEP LEARNING METHOD USED FOR CHARACTER RECOGNITIONIJCIRAS Journal
The field of Artificial Intelligence is very fashionable today, especially neural networks that work well in various areas such as speech recognition and natural language processing. This Research Article briefly describes how deep learning models work and what different techniques are used in text recognition. It also describes the great progress that has been made in the field of medicine, the analysis of forensic documents, the recognition of license plates, banking, health and the legal industry. The recognition of handwritten characters is one of the research areas in the field of artificial intelligence. The individual character recognition has a higher recognition accuracy than the complete word recognition. The new method for categorizing Freeman strings is presented using four connectivity events and eight connectivity events with a deep learning approach.
MultiModal Identification System in Monozygotic TwinsCSCJournals
With the increase in the number of twin births in recent decades, there is a need to develop alternate approaches that can secure the biometric system. In this paper an effective fusion scheme is presented that combines information presented by multiple domain experts based on the rank-level fusion integration method. The developed multimodal biometric system possesses a number of unique qualities, starting from utilizing Fisher’s Linear Discriminant methods for face matching, Principal Component Analysis for fingerprint matching and Local binary pattern features for iris matching and fused the information for effective recognition and authentication The importance of considering these boundary conditions, such as twins, where the possibility of errors is maximum will lead us to design a more reliable and robust security system.The proposed approach is tested on a real database consisting of 50 pair of identical twin images and shows promising results compared to other techniques. The Receiver Operating Characteristics also shows that the proposed method is superior compared to other techniques under study.
Multimodal Biometrics at Feature Level Fusion using Texture FeaturesCSCJournals
In recent years, fusion of multiple biometric modalities for personal authentication has received considerable attention. This paper presents a feature level fusion algorithm based on texture features. The system combines fingerprint, face and off-line signature. Texture features are extracted from Curvelet transform. The Curvelet feature dimension is selected based on d-prime number. The increase in feature dimension is reduced by using template averaging, moment features and by Principal component analysis (PCA). The algorithm is tested on in-house multimodal database comprising of 3000 samples and Chimeric databases. Identification performance of the system is evaluated using SVM classifier. A maximum GAR of 97.15% is achieved with Curvelet-PCA features.
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.
Feature Level Fusion of Multibiometric Cryptosystem in Distributed SystemIJMER
ABSTRACT: Multibiometrics is the combination of one or more biometrics (e.g., Fingerprint, Iris, and Face). Researchers
are focusing on how to provide security to the system, the template which was generated from the biometric need to be
protected. The problems of unimodal biometrics are solved by multibiometrics. The main objective is to provide a security to
the biometric template by generating a secure sketch by making use of multibiometric cryptosystem and which is stored in a
database. Once the biometric template is stolen it becomes a serious issue for the security of the system and also for user
privacy. In the existing approach, feature level fusion is used to combine the features securely with well-known biometric
cryptosystems namely fuzzy vault and fuzzy commitment. The drawbacks of existing system include accuracy of the biometric
need to be improved and the noises in the biometrics also need to be reduced. The proposed work is to enhance the security
using multibiometric cryptosystem in distributed system applications like e-commerce transactions, e-banking and ATM.
Keywords: Biometric Cryptosystem, Error correcting code, Fingerprint, Iris, Multibiometrics, Unimodal biometrics.
A SURVEY ON DEEP LEARNING METHOD USED FOR CHARACTER RECOGNITIONIJCIRAS Journal
The field of Artificial Intelligence is very fashionable today, especially neural networks that work well in various areas such as speech recognition and natural language processing. This Research Article briefly describes how deep learning models work and what different techniques are used in text recognition. It also describes the great progress that has been made in the field of medicine, the analysis of forensic documents, the recognition of license plates, banking, health and the legal industry. The recognition of handwritten characters is one of the research areas in the field of artificial intelligence. The individual character recognition has a higher recognition accuracy than the complete word recognition. The new method for categorizing Freeman strings is presented using four connectivity events and eight connectivity events with a deep learning approach.
An Indexing Technique Based on Feature Level Fusion of Fingerprint FeaturesIDES Editor
Personal identification system based on pass word
and other entities are ineffective. Nowadays biometric based
systems are used for human identification in almost many
real time applications. The current state-of-art biometric
identification focuses on accuracy and hence a good
performance result in terms of response time on small scale
database is achieved. But in today’s real life scenario biometric
database are huge and without any intelligent scheme the
response time should be high, but the existing algorithms
requires an exhaustive search on the database which increases
proportionally when the size of the database grows. This paper
addresses the problem of biometric indexing in the context of
fingerprint. Indexing is a technique to reduce the number of
candidate identities to be considered by the identification
algorithm. The fingerprint indexing methodology projected
in this work is based on a combination of Level 1, Level 2 and
Level-3 fingerprint features. The result shows the fusion of
level 1, level 2 and level 3 features gives better performance
and good indexing rate than with any one level of fingerprint
feature.
Bimodal Biometric System using Multiple Transformation Features of Fingerprin...IDES Editor
The biometric technology is used to identify
individuals effectively compared to existing traditional
methods. In this paper we propose Bimodal Biometric System
using Multiple Transformation features of Fingerprint and
Iris (BBMFI). The iris image is preprocessed to generate iris
template. The two level Discrete Wavelet Transformation
(DWT) is applied on iris template and Discrete Cosine
Transformation (DCT) is performed on second level low
frequency band to generate DCT coefficients which results in
features of iris. The fingerprint is preprocessed to obtain
Region of Interest (ROI) and segmented into four cells. Then
the DWT is applied on each cell to derive approximation band
and detailed bands. The Fast Fourier Transformation (FFT)
is applied on approximation band to compute absolute values
that results in features of fingerprint. The iris features and
fingerprint features are fused by concatenation to obtain final
set of features. The final feature vector of test and database
are compared using Euclidean distance matching. It is observed
that the values of Total Success Rate (TSR), False Rejection
Rate (FRR) and False Acceptance Rate (FAR) are improved in
the proposed system compared to existing algorithm.
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.
COMPUTER VISION FOR DATA CATALOGING IN ECOLOGICAL RESEARCHijma
Data collection is an essential, but time-consuming procedure in ecological research. An algorithm was developed by the author which incorporated two important computer vision techniques to automate butterfly cataloguing. Optical Character Recognition is used for character recognition and Contour Detection is used for image-processing. Proper pre-processing is first done on the images to improve accuracy of character recognition and butterfly measurement. Although there are limitations to Tesseract’s detection of certain fonts, overall, it can successfully identify words of basic fonts. Contour detection is an
advanced technique that can be utilized to measure an image. Multiple mathematical algorithms are used to calculate and determine the precise location of the points on which to draw the body and forewing lines of the butterfly. Overall, 92% accuracy are achieved by the program for the set of butterflies measured.
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.
Vision Based Gesture Recognition Using Neural Networks Approaches: A ReviewWaqas Tariq
The aim of gesture recognition researches is to create system that easily identifies gestures, and use them for device control, or convey in formations. In this paper we are discussing researches done in the area of hand gesture recognition based on Artificial Neural Networks approaches. Several hand gesture recognition researches that use Neural Networks are discussed in this paper, comparisons between these methods were presented, advantages and drawbacks of the discussed methods also included, and implementation tools for each method were presented as well.
Authentication of a person is the major concern in this era for security purposes. In biometric systems Signature is one of the behavioural features used for the authentication purpose. In this paper we work on the offline signature collected through different persons. Morphological operations are applied on these signature images with Hough transform to determine regular shape which assists in authentication process. The values extracted from this Hough space is used in the feed forward neural network which is trained using back-propagation algorithm. After the different training stages efficiency found above more than 95%. Application of this system will be in the security concerned fields, in the defence security, biometric authentication, as biometric computer protection or as method of the analysis of person’s behaviour changes.
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.
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
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.
Biometrics Authentication of Fingerprint with Using Fingerprint Reader and Mi...TELKOMNIKA JOURNAL
The idea of security is as old as humanity itself. Between oldest methods of security were
included simple mechanical locks whose authentication element was the key. At first, a universal–simple
type, later unique for each lock. A long time had mechanical locks been the sole option for protection
against unauthorized access. The boom of biometrics has come in the 20th century, and especially in
recent years, biometrics is much expanded in the various areas of our life. Opposite of traditional security
methods such as passwords, access cards, and hardware keys, it offers many benefits. The main benefits
are the uniqueness and the impossibility of their loss. The main benefits are the uniqueness and the
impossibility of their loss. Therefore we focussed in this paper on the the design of low cost biometric
fingerprint system and subsequent implementation of this system in praxtise. Our main goal was to create
a system that is capable of recognizing fingerprints from a user and then processing them. The main part
of this system is the microcontroller Arduino Yun with an external interface to the scan of the fingerprint
with a name Adafruit R305 (special reader). This microcontroller communicates with the external database,
which ensures the exchange of data between Arduino Yun and user application. This application was
created for (currently) most widespread mobile operating system-Android.
An Indexing Technique Based on Feature Level Fusion of Fingerprint FeaturesIDES Editor
Personal identification system based on pass word
and other entities are ineffective. Nowadays biometric based
systems are used for human identification in almost many
real time applications. The current state-of-art biometric
identification focuses on accuracy and hence a good
performance result in terms of response time on small scale
database is achieved. But in today’s real life scenario biometric
database are huge and without any intelligent scheme the
response time should be high, but the existing algorithms
requires an exhaustive search on the database which increases
proportionally when the size of the database grows. This paper
addresses the problem of biometric indexing in the context of
fingerprint. Indexing is a technique to reduce the number of
candidate identities to be considered by the identification
algorithm. The fingerprint indexing methodology projected
in this work is based on a combination of Level 1, Level 2 and
Level-3 fingerprint features. The result shows the fusion of
level 1, level 2 and level 3 features gives better performance
and good indexing rate than with any one level of fingerprint
feature.
Bimodal Biometric System using Multiple Transformation Features of Fingerprin...IDES Editor
The biometric technology is used to identify
individuals effectively compared to existing traditional
methods. In this paper we propose Bimodal Biometric System
using Multiple Transformation features of Fingerprint and
Iris (BBMFI). The iris image is preprocessed to generate iris
template. The two level Discrete Wavelet Transformation
(DWT) is applied on iris template and Discrete Cosine
Transformation (DCT) is performed on second level low
frequency band to generate DCT coefficients which results in
features of iris. The fingerprint is preprocessed to obtain
Region of Interest (ROI) and segmented into four cells. Then
the DWT is applied on each cell to derive approximation band
and detailed bands. The Fast Fourier Transformation (FFT)
is applied on approximation band to compute absolute values
that results in features of fingerprint. The iris features and
fingerprint features are fused by concatenation to obtain final
set of features. The final feature vector of test and database
are compared using Euclidean distance matching. It is observed
that the values of Total Success Rate (TSR), False Rejection
Rate (FRR) and False Acceptance Rate (FAR) are improved in
the proposed system compared to existing algorithm.
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.
COMPUTER VISION FOR DATA CATALOGING IN ECOLOGICAL RESEARCHijma
Data collection is an essential, but time-consuming procedure in ecological research. An algorithm was developed by the author which incorporated two important computer vision techniques to automate butterfly cataloguing. Optical Character Recognition is used for character recognition and Contour Detection is used for image-processing. Proper pre-processing is first done on the images to improve accuracy of character recognition and butterfly measurement. Although there are limitations to Tesseract’s detection of certain fonts, overall, it can successfully identify words of basic fonts. Contour detection is an
advanced technique that can be utilized to measure an image. Multiple mathematical algorithms are used to calculate and determine the precise location of the points on which to draw the body and forewing lines of the butterfly. Overall, 92% accuracy are achieved by the program for the set of butterflies measured.
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.
Vision Based Gesture Recognition Using Neural Networks Approaches: A ReviewWaqas Tariq
The aim of gesture recognition researches is to create system that easily identifies gestures, and use them for device control, or convey in formations. In this paper we are discussing researches done in the area of hand gesture recognition based on Artificial Neural Networks approaches. Several hand gesture recognition researches that use Neural Networks are discussed in this paper, comparisons between these methods were presented, advantages and drawbacks of the discussed methods also included, and implementation tools for each method were presented as well.
Authentication of a person is the major concern in this era for security purposes. In biometric systems Signature is one of the behavioural features used for the authentication purpose. In this paper we work on the offline signature collected through different persons. Morphological operations are applied on these signature images with Hough transform to determine regular shape which assists in authentication process. The values extracted from this Hough space is used in the feed forward neural network which is trained using back-propagation algorithm. After the different training stages efficiency found above more than 95%. Application of this system will be in the security concerned fields, in the defence security, biometric authentication, as biometric computer protection or as method of the analysis of person’s behaviour changes.
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.
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
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.
Biometrics Authentication of Fingerprint with Using Fingerprint Reader and Mi...TELKOMNIKA JOURNAL
The idea of security is as old as humanity itself. Between oldest methods of security were
included simple mechanical locks whose authentication element was the key. At first, a universal–simple
type, later unique for each lock. A long time had mechanical locks been the sole option for protection
against unauthorized access. The boom of biometrics has come in the 20th century, and especially in
recent years, biometrics is much expanded in the various areas of our life. Opposite of traditional security
methods such as passwords, access cards, and hardware keys, it offers many benefits. The main benefits
are the uniqueness and the impossibility of their loss. The main benefits are the uniqueness and the
impossibility of their loss. Therefore we focussed in this paper on the the design of low cost biometric
fingerprint system and subsequent implementation of this system in praxtise. Our main goal was to create
a system that is capable of recognizing fingerprints from a user and then processing them. The main part
of this system is the microcontroller Arduino Yun with an external interface to the scan of the fingerprint
with a name Adafruit R305 (special reader). This microcontroller communicates with the external database,
which ensures the exchange of data between Arduino Yun and user application. This application was
created for (currently) most widespread mobile operating system-Android.
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.
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.
ijerst offers a fast publication schedule whilst maintaining rigorous peer review; the use of recommended electronic formats for article delivery expedites the process. Editorial Board or others working in the field as appropriate, to ensure they are likely to be of the level of interest and importance appropriate for the journal. International Journal of Engineering Research and Science & Technology (IJERST) is an international online journal in English published Quarterly. All submitted research articles are subjected to immediate rapid screening by the editors.
ijerst offers a fast publication schedule whilst maintaining rigorous peer review; the use of recommended electronic formats for article delivery expedites the process. International Journal of Engineering Research and Science & Technology (IJERST) is an international online journal in English published Quarterly. All submitted research articles are subjected to immediate rapid screening by the editors, in consultation with the Editorial Board or others working in the field as appropriate, to ensure they are likely to be of the level of interest and importance appropriate for the journal.
Hybrid Approach for Brain Tumour Detection in Image Segmentationijtsrd
In this paper we have considered illustrating a few techniques. But the numbers of techniques are so large they cannot be all addressed. Image segmentation forms the basics of pattern recognition and scene analysis problems. The segmentation techniques are numerous in number but the choice of one technique over the other depends only on the application or requirements of the problem that is being considered. Analysis of cluster is a descriptive assignment that perceive homogenous group of objects and it is also one of the fundamental analytical method in facts mining. The main idea of this is to present facts about brain tumour detection system and various data mining methods used in this system. This is focuses on scalable data systems, which include a set of tools and mechanisms to load, extract, and improve disparate data power to perform complex transformations and analysis will be measured between the way of measuring the Furrier and Wavelet Transform distance. Sandeep | Jyoti Kataria "Hybrid Approach for Brain Tumour Detection in Image Segmentation" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-4 | Issue-6 , October 2020, URL: https://www.ijtsrd.com/papers/ijtsrd33409.pdf Paper Url: https://www.ijtsrd.com/medicine/other/33409/hybrid-approach-for-brain-tumour-detection-in-image-segmentation/sandeep
IOSR Journal of Electronics and Communication Engineering(IOSR-JECE) is an open access international journal that provides rapid publication (within a month) of articles in all areas of electronics and communication engineering and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications in electronics and communication engineering. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
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.
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.
As we know the fingerprint is unique of every living objects. It is quite difficult to find out the prints.
Usually the Forensics use Fine powder and duct tapes to identify the prints of living object. As powder is
exceptionally muddled, so such molecule can cause loss of information after that examination the information is
coordinated with the system. The proposed system consists of an embedded device in which it consists of ultra
light to glow the fingerprints details. After that we can detect the fingerprint, analysis and it will checks on the
database, and it will return the output after matching. For matching and analysis of the Fingerprint, we will be
using the Algorithm for matching.
The Art Pastor's Guide to Sabbath | Steve ThomasonSteve Thomason
What is the purpose of the Sabbath Law in the Torah. It is interesting to compare how the context of the law shifts from Exodus to Deuteronomy. Who gets to rest, and why?
Instructions for Submissions thorugh G- Classroom.pptxJheel Barad
This presentation provides a briefing on how to upload submissions and documents in Google Classroom. It was prepared as part of an orientation for new Sainik School in-service teacher trainees. As a training officer, my goal is to ensure that you are comfortable and proficient with this essential tool for managing assignments and fostering student engagement.
Synthetic Fiber Construction in lab .pptxPavel ( NSTU)
Synthetic fiber production is a fascinating and complex field that blends chemistry, engineering, and environmental science. By understanding these aspects, students can gain a comprehensive view of synthetic fiber production, its impact on society and the environment, and the potential for future innovations. Synthetic fibers play a crucial role in modern society, impacting various aspects of daily life, industry, and the environment. ynthetic fibers are integral to modern life, offering a range of benefits from cost-effectiveness and versatility to innovative applications and performance characteristics. While they pose environmental challenges, ongoing research and development aim to create more sustainable and eco-friendly alternatives. Understanding the importance of synthetic fibers helps in appreciating their role in the economy, industry, and daily life, while also emphasizing the need for sustainable practices and innovation.
Ethnobotany and Ethnopharmacology:
Ethnobotany in herbal drug evaluation,
Impact of Ethnobotany in traditional medicine,
New development in herbals,
Bio-prospecting tools for drug discovery,
Role of Ethnopharmacology in drug evaluation,
Reverse Pharmacology.
Read| The latest issue of The Challenger is here! We are thrilled to announce that our school paper has qualified for the NATIONAL SCHOOLS PRESS CONFERENCE (NSPC) 2024. Thank you for your unwavering support and trust. Dive into the stories that made us stand out!
Palestine last event orientationfvgnh .pptxRaedMohamed3
An EFL lesson about the current events in Palestine. It is intended to be for intermediate students who wish to increase their listening skills through a short lesson in power point.
2. 44 International Journal of Engineering & Technology
2. General cuckoo-search algorithm
Cuckoo search uses the following representations:
Each egg in a nest represents a solution, and a cuckoo egg
represents a new solution. The aim is to use the new and
potentially better solutions (cuckoos) to replace a not-so-good
solution in the nests. In the simplest form, each nest has one egg.
The algorithm can be extended to more complicated cases in
which each nest has multiple eggs representing a set of solutions.
CS is based on three idealized rules:
1. Each cuckoo lays one egg at a time, and dumps its egg
in a randomly chosen nest;
2. The best nests with high quality of eggs will carry over
to the next generation;
3. The number of available hosts nests is fixed, and the egg
laid by a cuckoo is discovered by the host bird with a
probability Pa ∈ (0,1). [1]
begin
Objective function f(x), x = (x1, ..., xd) ^T
Generate initial population of n host nests xi (i = 1, 2, ..., n).
while (t <MaxGeneration) or (stop criterion)
Get a cuckoo randomly by L´evy flights evaluate its
quality/fitness Fi.
Choose a nest among n (say, j) randomly
if (Fi > Fj)
replace j by the new solution;
end
A fraction (pa) of worse nests are abandoned and new ones are
built;
Keep the best solutions (or nests with quality solutions);
Rank the solutions and find the current best
end while
Postprocess results and visualization
End
3. Fingerprint analysis
Fingerprint recognition
Human Fingerprints are unique, difficult to alter and durable.
Fingertips contain ridges and valleys which forms distinctive
patterns. Fingerprints are distinguished by certain features called
Minutiae. Among the various types of minutia, the following are
most significantly used:
• Ridge ending-the abrupt end of a ridge
• Ridge bifurcation- a single ridge that divides into two
Fig. 1: Types of minutiae
A fingerprint recognition system consists of fingerprint acquiring
device, minutia extractor and minutia matcher.
Fingerprint acquisition
A Fingerprint sensor is used to capture a digital image of the
fingerprint. The image processed to create a biometric template
which is stored and used for matching with previously stored
templates. Commonly used Fingerprint sensors include optical,
capacitive, thermal, piezo resistive and ultrasonic.
Fingerprint image is enhanced to obtain a clear Image. Various
Image enhancement techniques are employed to reduce the noise
and enhance the definition of ridges against valleys. Then the
Minutia is extracted and compared with a template stored.
Histogram equalization
Histogram equalization is a technique for adjusting image
intensities to enhance contrast by adjusting the intensity
distribution on a histogram. This allows areas of lower local
contrast to gain a higher contrast without affecting the global
contrast. This method is useful in images with backgrounds and
foregrounds that are both bright or both dark. [2]
Binarization
Fingerprint-Image-Binarization transforms a gray image to a 1-bit
binarized image. Most minutiae extraction algorithms operate on
binary images where there are only two levels of interest: the
black pixels which represents ridges and the white pixels which
represents the valleys. This Improves the Contract between the
ridges and valleys. [3]
Thinning
Thinning is a morphological operation that successively erodes
away foreground pixels until they are one-pixel wide. Thinning is
normally only applied to binary images, and produces another
binary image as output. It is the final step prior to minutiae
extraction. [3]
Minutiae extraction
This method extracts the ridge endings and bifurcations from the
skeleton image by examining the local neighbourhood of each
ridge pixel using a 3×3 window. The ridge can be divided into
bifurcation, ridge ending and non-minutiae point based on it.
Fig. 2: Binarized ridge ending
Fig. 3: Binarized Ridge bifurcation
Minutiae matching
Minutiae Obtained are plotted in a matrix form and a cuckoo
search based matching algorithm is employed. The eggs are taken
as sub matrix of the fingerprint 1-bit grey scale image. The eggs
which survives are taken as the next generation cuckoo which
again lays eggs. They new eggs laid are of greater dimension
matrix in which the previous generation elements are also a
subset. The cuckoo will be killed at an instance when the
anomality is detected i.e. when the required level of significance is
obtained the cuckoo survives else the vice versa.
The cuckoos will lay eggs till a most significant match of
fingerprint is obtained.
4. Optimized fingerprint recognition
algorithm
Algorithm to obtain sub-matrices from a single 1 – bit greyscale
fingerprint image matrix.
Step 1: Start
Step 2: Get matrix dimension.
Step 3: if matrix_dimension is even
Set i as 3
else
Set i as 2
Step 4: Initialise generation as 1
3. International Journal of Engineering & Technology 45
Step 5: Calculate offset,
offset = ( matrix_dimension – i ) / 2
Step 6: initialise row_start and column_start as Offset
Step 7: initialise row_end and column_end as Offset + i
Step 8: Initialise sub-matrix as
Matrix[row_start : row_end ] [ column_start :
column_end ]
Step 9: increment i by 2
Step 10: incement generation by 1
Step 11: if i < matrix_dimension
Repeat steps 5 to 11
Step 12: Stop
Cuckoo search algorithm in fingerprint recognition
begin
y = fingerprint to be matched
Generate initial population of n images xi (i = 1, 2, ..., n)
while (till n images)
while (CurrentGeneration < MaxGeneration)
xi = submatrix corresponding to current generation
y = submatrix corresponding to current generation
if (xi and y matches)
image is taken to next generation
else
image is not taken to next generation
break while loop
end if
next generation
end while
next image
end while
Postprocess results
end
5. Simulation and results
The 1-bit grayscale image of the finger print is represented as a
square matrix with 1’s and 0’s. The sub-matrix identification
algorithm is simulated using c language taking the 1-bit gray scale
image as a 2-dimensional array. The simulation displays the
element in the sub-matrix as the pair of subscript (ie. Row
subscript followed by Column subscript) and the subscript ranges
from 0 to n-1 , where n is the dimension of the matrix.
Simulating sub-matrix algorithm
Enter Matrix dimension: 10
Even dimension
Taking the following as 1-bit fingerprint image matrix dimension
[0][0] [0][1] [0][2] [0][3] [0][4] [0][5] [0][6] [0][7] [0][8] [0][9]
[1][0] [1][1] [1][2] [1][3] [1][4] [1][5] [1][6] [1][7] [1][8] [1][9]
[2][0] [2][1] [2][2] [2][3] [2][4] [2][5] [2][6] [2][7] [2][8] [2][9]
[3][0] [3][1] [3][2] [3][3] [3][4] [3][5] [3][6] [3][7] [3][8] [3][9]
[4][0] [4][1] [4][2] [4][3] [4][4] [4][5] [4][6] [4][7] [4][8] [4][9]
[5][0] [5][1] [5][2] [5][3] [5][4] [5][5] [5][6] [5][7] [5][8] [5][9]
[6][0] [6][1] [6][2] [6][3] [6][4] [6][5] [6][6] [6][7] [6][8] [6][9]
[7][0] [7][1] [7][2] [7][3] [7][4] [7][5] [7][6] [7][7] [7][8] [7][9]
[8][0] [8][1] [8][2] [8][3] [8][4] [8][5] [8][6] [8][7] [8][8] [8][9]
[9][0] [9][1] [9][2] [9][3] [9][4] [9][5] [9][6] [9][7] [9][8] [9][9]
For i = 3 Generation:1
[3][3] [3][4] [3][5] [3][6]
[4][3] [4][4] [4][5] [4][6]
[5][3] [5][4] [5][5] [5][6]
[6][3] [6][4] [6][5] [6][6]
For i = 5 Generation:2
[2][2] [2][3] [2][4] [2][5] [2][6] [2][7]
[3][2] [3][3] [3][4] [3][5] [3][6] [3][7]
[4][2] [4][3] [4][4] [4][5] [4][6] [4][7]
[5][2] [5][3] [5][4] [5][5] [5][6] [5][7]
[6][2] [6][3] [6][4] [6][5] [6][6] [6][7]
[7][2] [7][3] [7][4] [7][5] [7][6] [7][7]
For i = 7 Generation:3
[1][1] [1][2] [1][3] [1][4] [1][5] [1][6] [1][7] [1][8]
[2][1] [2][2] [2][3] [2][4] [2][5] [2][6] [2][7] [2][8]
[3][1] [3][2] [3][3] [3][4] [3][5] [3][6] [3][7] [3][8]
[4][1] [4][2] [4][3] [4][4] [4][5] [4][6] [4][7] [4][8]
[5][1] [5][2] [5][3] [5][4] [5][5] [5][6] [5][7] [5][8]
[6][1] [6][2] [6][3] [6][4] [6][5] [6][6] [6][7] [6][8]
[7][1] [7][2] [7][3] [7][4] [7][5] [7][6] [7][7] [7][8]
[8][1] [8][2] [8][3] [8][4] [8][5] [8][6] [8][7] [8][8]
Enter Matrix dimension: 9
Odd dimension
Taking the following as 1-bit fingerprint image matrix dimension
[0][0] [0][1] [0][2] [0][3] [0][4] [0][5] [0][6] [0][7] [0][8]
[1][0] [1][1] [1][2] [1][3] [1][4] [1][5] [1][6] [1][7] [1][8]
[2][0] [2][1] [2][2] [2][3] [2][4] [2][5] [2][6] [2][7] [2][8]
[3][0] [3][1] [3][2] [3][3] [3][4] [3][5] [3][6] [3][7] [3][8]
[4][0] [4][1] [4][2] [4][3] [4][4] [4][5] [4][6] [4][7] [4][8]
[5][0] [5][1] [5][2] [5][3] [5][4] [5][5] [5][6] [5][7] [5][8]
[6][0] [6][1] [6][2] [6][3] [6][4] [6][5] [6][6] [6][7] [6][8]
[7][0] [7][1] [7][2] [7][3] [7][4] [7][5] [7][6] [7][7] [7][8]
[8][0] [8][1] [8][2] [8][3] [8][4] [8][5] [8][6] [8][7] [8][8]
For i = 2 Generation:1
[3][3] [3][4] [3][5]
[4][3] [4][4] [4][5]
[5][3] [5][4] [5][5]
For i = 4 Generation:2
[2][2] [2][3] [2][4] [2][5] [2][6]
[3][2] [3][3] [3][4] [3][5] [3][6]
[4][2] [4][3] [4][4] [4][5] [4][6]
[5][2] [5][3] [5][4] [5][5] [5][6]
4. 46 International Journal of Engineering & Technology
[6][2] [6][3] [6][4] [6][5] [6][6]
For i = 8 Generation:4
[0][0] [0][1] [0][2] [0][3] [0][4] [0][5] [0][6] [0][7] [0][8]
[1][0] [1][1] [1][2] [1][3] [1][4] [1][5] [1][6] [1][7] [1][8]
[2][0] [2][1] [2][2] [2][3] [2][4] [2][5] [2][6] [2][7] [2][8]
[3][0] [3][1] [3][2] [3][3] [3][4] [3][5] [3][6] [3][7] [3][8]
[4][0] [4][1] [4][2] [4][3] [4][4] [4][5] [4][6] [4][7] [4][8]
[5][0] [5][1] [5][2] [5][3] [5][4] [5][5] [5][6] [5][7] [5][8]
[6][0] [6][1] [6][2] [6][3] [6][4] [6][5] [6][6] [6][7] [6][8]
[7][0] [7][1] [7][2] [7][3] [7][4] [7][5] [7][6] [7][7] [7][8]
[8][0] [8][1] [8][2] [8][3] [8][4] [8][5] [8][6] [8][7] [8][8]
6. Conclusion and future work
The recognition of behavioral biometrics includes more complex
data and that is something which requires optimization than that of
physical biometrics. If the behavioral biometric recognition gets
optimized it can help in various fields which include medical and
security. We would continue to work on using cuckoo search to
optimize behavioral biometrics such as walking pattern, writing
pattern.
Fingerprint Search Algorithm using cuckoo search is efficient
since the prints compared the prints in an incremental way starting
from the center. Thus, an optimized algorithm is produced using
Cuckoo Search. Since Fingerprints are represented as a 2d matrix
the effectiveness of an optimized algorithm is insignificant.
While in case of More Complex Biometric Features like Walking
pattern, Writing Style, etc. Many Variables and Environmental
factors are involved. Then an Optimized algorithm becomes an
absolute necessity. Complex Biometric Algorithms can also be
optimized using cuckoo search. By Optimizing using Cuckoo
Search, the time taken to find a complete match from the database
is reduced drastically and thus increasing the overall efficiency of
the system.
References
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[3] Erbilek M & Fairhurst M, “A methodological framework for
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