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For large fingerprint database, classification process is an important step for matching with other fingerprint, which can provide an indexing mechanism. In this work, fingerprint classification based on the Gray-Level Fuzzy Clustering Co-Occurrence Matrixis proposed. Using Gray-Level Fuzzy clustering co-occurrence matrices provide representing the...
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... of fingerprints were firstly made by Galton [1] and Henry [2] whom devised very similar fingerprint classification systems. Galton described his classification system that includes three main fingerprint patterns -loops, whorls and arches. Whereas, Henry defined eight classes: whorl, Plain Arch, Right Loop, Left Loop, Central Pocket, Tented Arch, Twin Loop, and Accident but left loops, right loops and whorls are generally used types and these classes include nearly 94% of fingerprints. Because of these data, we can investigate in four major classes. These classes are left loop, right loop, whorl and arch, and this work aims classifying in these classes. The most commonly used fingerprint classes are shown in Fig. 1. ...
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Fingerprint is one of the broadly utilized biometric distinguishing proof to recognize the persons due steady and worthiness. The classification of fingerprints gives indexing to the dataset to decrease the seeking and matching manner. There researches have been developed numerous approaches for fingerprint classification model, for example, the Ne...
Understanding complex events from unstructured video, like scoring a goal in a football game, is an extremely challenging task due to the dynamics, complexity and variation of video sequences. In this work, we attack this problem exploiting the capabilities of the recently developed framework of deep learning. We consider independently encoding spa...
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... In order to determine that the two fingerprints belong to one person, they must agree in the form (arcs, slopes), in the shape of the angle and the centre, in the amplitude, and in the presence of any traces of wounds or scars, and in the sub-characteristics of the lines forming the imprint in terms of the beginning and end of these lines and their deviation, branching or merging in another line, or islands are in the way of the line. It is often sufficient to have twelve points of agreement to say that the two fingerprints are the same, although obtaining a greater number of points of agreement is often possible [17], [18]. ...
... This device is an array of light-sensing diodes-photo sites that can generate electrical signals in response to the units of light. The job of each of these photo sites is to record a single pixel, which is a minor point representing the light that hits that spot [16], [17]. Can be illustrated in Figure 3. ...
... Design and develop authentication in electronic payment systems based on … (Ahmed Abdulkarim Talib) Types of fingerprint[17] ...
Biometrics is a highly reliable technology where it has become possible to
use the characteristics of a person or user (biometrics) along with traditional
passwords, and we can even say that it has become an indispensable
complement in modern authentication systems today, especially with regard
to bank accounts, banks, financial technology (FinTech) internet of things
(IoT) devices and all a process related to money and privacy, and biometric
methods are multiple and increasing day by day, the most famous of which
is (iris, face chart, palm, fingerprint, and others). Biometric systems are
immune and immune from modern electronic attacks, such as plagiarism or
electronic theft, because the authentication here takes place when all
conditions are met. Then the authentication is done and the process is
completed, and the aim is to reach the highest levels of accuracy and security
and to make the user more comfortable to deal with these modern systems
that provide him with many advantages and high privacy.
... [1][2][3]. Clustering has been applied to problems in a variety of areas, including exploratory data mining [4], image processing [5,6], disease diagnostic [7], astronomy [8], genetic [9] and, mathematical programming [10], etc. Data clustering approaches can be grouped into two types. ...
Data Clustering stands for a group of methods classifying patterns into groups and retrieving similarities or dissimilarities of a collection of objects. Clustering is used for pattern recognition, machine learning, etc. One of the approaches to clustering is optimization. The aim of the optimization is finding the best solution in the search space of a problem as much as possible. Many optimization methods were modified to solve clustering problems in literature. Gray Wolf Optimizer (GWO) is one of the nature-inspired meta-heuristic algorithms simulating the hunting of gray wolves. GWO has applied to solve several optimization issues in different fields. In this study, GWO was examined in the case of data clustering. GWO was modified to get better clustering results and applied to well-known benchmark data sets. The performance of GWO was compared to the other algorithms used as clustering. The results show that GWO can be used for data clustering successfully.
... Consequently, artificial intelligent techniques based on MPPT have been proposed to solve the significant problems of the classical MPPT methods [21]. In addition, these techniques do not need accurate parameters or complex mathematics when managing the system [22,23]. In particular, the FL-MPPT technique is one of the most powerful controllers for a PV system due to its high converging speed and low fluctuation around the MPP [24,25]. ...
Maximum power point tracking (MPPT) techniques are considered a crucial part in photovoltaic system design to maximise the output power of a photovoltaic array. Whilst several techniques have been designed, Perturb and Observe (P&O) is widely used for MPPT due to its low cost and simple implementation. Fuzzy logic (FL) is another common technique that achieves vastly improved performance for MPPT technique in terms of response speed and low fluctuation about the maximum power point. However, major issues of the conventional FL-MPPT are a drift problem associated with changing irradiance and complex implementation when compared with the P&O-MPPT. In this paper, a novel MPPT technique based on FL control and P&O algorithm is presented. The proposed method incorporates the advantages of the P&O-MPPT to account for slow and fast changes in solar irradiance and the reduced processing time for the FL-MPPT to address complex engineering problems when the membership functions are few. To evaluate the performance, the P&O-MPPT, FL-MPPT and the proposed method are simulated by a MATLAB-SIMULINK model for a grid-connected PV system. The EN 50530 standard test is used to calculate the efficiency of the proposed method under varying weather conditions. The simulation results demonstrate that the proposed technique accurately tracks the maximum power point and avoids the drift problem, whilst achieving efficiencies of greater than 99.6%.
... Dermatoglyphics has been considered as a genetic marker in many congenital and clinical diseases such as Down's syndrome, Apert syndrome, and Diabetes. [13]The Role of dermatoglyphics as an indicator of precancerous and cancerous lesions of the oral cavity was studied by Ambika [23]. Similar studies have been carried out by Satish et al(2014), [24] and SNR Yaratha(2017), [25]co-relating dermatoglyphics and cheiloscopy with Oral Submucous Fibrosis and Cleft lip and palate respectively. ...
Dental Caries and Periodontitis are two of the commonest oral ailments affecting millions of people worldwide. Though there are some known causative factors, mystery still revolves around the fact that some individuals are more susceptible to it compared to others, who are exposed to similar conditions. This can be partially explained by the fact that these diseases are genetically linked. And apart from the regular oral hygiene measures, the only way to prevent these diseases is by predicting its occurrence and taking necessary measures to limit its destruction potential. It is a known fact that the epithelium of finger buds, the lips, and the tooth develop at the same time of intrauterine life. So our study was an attempt to correlate the occurrence of Dental caries and/ or Periodontitis in an individual, with their lip print and thumbprint patterns, and to assess whether these investigation tools can be used to predict the occurrence of these diseases at an early age Aim: To study the role of cheiloscopy and dermatoglyphics as predictive factors for dental caries and periodontal disease in an adult institutional population (age >12 years). Materials and Methods: A cross-sectional study was carried out on 200 patients reporting to the OPD of Oral Medicine and Radiology department, NAIR HOSPITAL DENTAL COLLEGE, MUMBAI. They were screened based on the criteria laid down for the study and were divided into four groups(Group 1: DMFT(Decayed Missing Filled Teeth Index) score of 7 or more, Group 2: CPITN(Community Periodontal Index of Treatment Needs) score of 2 or more in more than 2 sextants, Group 3: DMFT score of 7 or more and CPITN score of 2 or more in more than 2 sextants, Group 4: Control Group), following which their lip print and thumbprint patterns were recorded and data was analyzed using SPSS version 16.0 and Mann-Whitney U test was used to compare types of lip pattern and thumbprints between the different experimental groups Results: The prevalence of Reticular pattern was maximum in subjects with Dental Caries (50%) and the ones with both Caries and Periodontitis (50%). Also, a significant relation was found between the left thumbprint pattern and oral health status, with the left loop pattern (71.4%) being the commonest in subjects having both Dental Caries and Periodontal disease. On the other hand, Significant results weren't found with respect to the right thumbprint pattern. Conclusion: Dermatoglyphics and Cheiloscopy can hence prove to be extremely useful, noninvasive and inexpensive tools for preliminary investigations and early detection of oral diseases.
... The update process is not made for every situation; if the number of changes in the past 50 frames is lower than 1, values belonging to that block remain the same. This part of algorithm has significant effect on total performance of algorithm [32]. So, we reduce the time spent in the normalization process. ...
Today, determining background which forms the basis of the video surveillance system whose use is increasing in parallel with developing technology, is a complicated process to implement for cases involving dynamic scene. In this study, we proposed a block-based adaptive method which can be adaptable to dynamic environmental conditions. By grouping the pixels in the picture frame as 2 × 2 non-overlapped blocks, we reduced the amount of noise and the time delay caused by processing of pixels. By a simple counter structure, we created an adaptive threshold parameter which can be adapted according to the case in N surrounding. We used this parameter to perform an update of the background model and reduced background model normalization process. So, we reduced the update time of background operably. Our proposed method achieved successful results in levels of grey levels.
... The created model classifies an unknown sample for the learned class in the training set. In literature, some algorithms such as DT, fuzzy clustering, NN and Naïve Bayes have been proposed for classification [16][17][18][19]. In this paper, NN and DT classification tools are used. ...
Data mining is the process of finding meaningful data from large data stacks with the help of intelligent methods. In many areas such as biology, genetics, finance, medicine and engineering, data mining is used to obtain meaningful results from data. Knowing the characteristics of the data of the subject studied increases the success of data mining techniques. In this study, different data mining techniques, Neural Network (NN) and Decision Tree (DT), are used for diagnosis of diabete disease. The dataset for this study are obtained from Pima Indians Diabetes database. To increase classification performance, the samples in database are normalized. Normalization process for the diagnosis of diabetes is made according to the criteria of international organizations. The normalized samples are used for training and testing of NN and DT. Performances of both data mining techniques are investigated by depending on classification accuracy. The obtained results are also compared with that of the previous studies for better validation. The results of this study show that DT using normalized samples is more effective than NN using normalized samples as well as previous studies.
A contactless fingerprint is a novel approach to fingerprint recognition, that originated after the covid-19 pandemic because of hygiene issues. In contactless and contact-based fingerprint matching several patterns and features are used to study the ridge-valley patterns of the fingertip. So, the performance of a fingerprint matching system depends on the feature extraction phase. Therefore, feature selection should be done cautiously. Over the period, numerous features and corresponding approaches have been developed for fingerprint recognition. Selecting one or more features is a crucial step in fingerprint identification, which depends upon the database and type of application (like military, commercial, etc.). Hence, the purpose of this study is to do a comprehensive assessment of the available features for matching contact-based and contactless fingerprints.
This paper addresses the characteristics, technology, and possible future of fingerprints authentication method. Fingerprint physiology makes it an ideal for biometrics authentication, primarily the tiny details located on its surface called minutiae. Fingerprint scanning systems are designed to detect minutiae. Images of detected minutiae are processed through matching algorithms in order to verify a query fingerprint that is identical to a stored fingerprint. However, fingerprint authentication based on minutiae can be easily bypassed and the need for a more secure method is required. With respect to the issue, this work explores the possibility of detecting the thickness of the skin layer within a fingerprint as a method of biometrics authentication. Current thickness measuring methods that are non-invasive for that task are identified as Laser Scanning Microscopy (LSM), Optical Coherence Tomography (OCT) and Near Infrared Spectroscopy (NIR). Of the three listed, only OCT and NIR methodology seems viable for simple yet reliable use and can become as promising methods for authentication based on skin layer thickness.
