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Optimization Techniques for Human Multi-Biometric Recognition System
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Researchers are increasingly using multimodal biometrics to strengthen the security of biometric applications. In this study, a strong multimodal human identification model was developed to address the growing problem of spoofing attacks in biometric security systems. Through the use of metaheuristic optimization methods, such as the Genetic Algorithm(GA), Ant Colony Optimization(ACO), and Particle Swarm Optimization (PSO) for feature selection, this unique model incorporates three biometric modalities: face, iris, and fingerprint. Image pre-processing, feature extraction, critical image feature selection, and multibiometric recognition are the four main steps in the workflow of the system. To determine its performance, the model was evaluated on the SDUMLA-HMT dataset, which contains a variety of biometric features from various individuals. The system outperformed existing techniques in the literature with an excellent recognition accuracy of 99.4%. Although this result is encouraging, further research on larger and more varied datasets is necessary to confirm its applicability across many circumstances. This study highlights how multimodal biometrics strengthened by metaheuristic algorithms can considerably increase biometric security against spoofing assaults, thereby opening a promising new direction for future development in the field.

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Publication Date
Thu Oct 01 2015
Journal Name
Engineering And Technology Journal
Genetic Based Optimization Models for Enhancing Multi- Document Text Summarization
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Publication Date
Sun Feb 27 2022
Journal Name
Iraqi Journal Of Science
A Multi-Objective Task Offloading Optimization for Vehicular Fog Computing
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      Internet of Vehicle (IoV) is one of the most basic branches of the Internet of Things (IoT), which provides many advantages for drivers and passengers to ensure safety and traffic efficiency. Most IoV applications are delay-sensitive and require resources for data storage and computation that cannot be afforded by vehicles. Thus, such tasks are always offloaded to more powerful nodes, like cloud or fog. Vehicular Fog Computing (VFC), which extends cloud computing and brings resources closer to the edge of the network, has the potential to reduce both traffic congestion and load on the cloud. Resources management and allocation process is very critical for satisfying both user and provider needs. However, th

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Publication Date
Thu Nov 29 2018
Journal Name
Iraqi Journal Of Science
Improving Extractive Multi-Document Text Summarization Through Multi-Objective Optimization
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Multi-document summarization is an optimization problem demanding optimization of more than one objective function simultaneously. The proposed work regards balancing of the two significant objectives: content coverage and diversity when generating summaries from a collection of text documents.

     Any automatic text summarization system has the challenge of producing high quality summary. Despite the existing efforts on designing and evaluating the performance of many text summarization techniques, their formulations lack the introduction of any model that can give an explicit representation of – coverage and diversity – the two contradictory semantics of any summary. In this work, the design of

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Publication Date
Fri Jun 29 2018
Journal Name
Journal Of The College Of Education For Women
HandWritten Numerals Recognition System
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  Recognition is one of the basic characteristics of human brain, and also for the living   creatures. It is possible to recognize images, persons, or patterns according to their characteristics. This recognition could be done using eyes or dedicated proposed methods. There are numerous applications for pattern recognition such as recognition of printed or handwritten letters, for example reading post addresses automatically and reading documents or check reading in bank.

      One of the challenges which faces researchers in character recognition field is the recognition of digits, which are written by hand. This paper describes a classification method for on-line handwrit

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Publication Date
Fri Jul 18 2014
Journal Name
International Journal Of Computer Applications
3-Level Techniques Comparison based Image Recognition
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Image recognition is one of the most important applications of information processing, in this paper; a comparison between 3-level techniques based image recognition has been achieved, using discrete wavelet (DWT) and stationary wavelet transforms (SWT), stationary-stationary-stationary (sss), stationary-stationary-wavelet (ssw), stationary-wavelet-stationary (sws), stationary-wavelet-wavelet (sww), wavelet-stationary- stationary (wss), wavelet-stationary-wavelet (wsw), wavelet-wavelet-stationary (wws) and wavelet-wavelet-wavelet (www). A comparison between these techniques has been implemented. according to the peak signal to noise ratio (PSNR), root mean square error (RMSE), compression ratio (CR) and the coding noise e (n) of each third

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Publication Date
Sun Apr 30 2023
Journal Name
Iraqi Journal Of Science
A Genetic Based Optimization Model for Extractive Multi-Document Text Summarization
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Extractive multi-document text summarization – a summarization with the aim of removing redundant information in a document collection while preserving its salient sentences – has recently enjoyed a large interest in proposing automatic models. This paper proposes an extractive multi-document text summarization model based on genetic algorithm (GA). First, the problem is modeled as a discrete optimization problem and a specific fitness function is designed to effectively cope with the proposed model. Then, a binary-encoded representation together with a heuristic mutation and a local repair operators are proposed to characterize the adopted GA. Experiments are applied to ten topics from Document Understanding Conference DUC2002 datas

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Publication Date
Sun Sep 24 2023
Journal Name
Journal Of Al-qadisiyah For Computer Science And Mathematics
Human Recognition Using Ear Features: A Review
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Over the past few years, ear biometrics has attracted a lot of attention. It is a trusted biometric for the identification and recognition of humans due to its consistent shape and rich texture variation. The ear presents an attractive solution since it is visible, ear images are easily captured, and the ear structure remains relatively stable over time.  In this paper, a comprehensive review of prior research was conducted to establish the efficacy of utilizing ear features for individual identification through the employment of both manually-crafted features and deep-learning approaches. The objective of this model is to present the accuracy rate of person identification systems based on either manually-crafted features such as D

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Publication Date
Mon Oct 30 2023
Journal Name
Traitement Du Signal
A Comprehensive Review on Machine Learning Approaches for Enhancing Human Speech Recognition
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Publication Date
Wed Aug 01 2012
Journal Name
I-manger's Journal On Information Technology
A MODULE FOR ENHANCING RECOGNITION SYSTEM FOR QR CODE SCANNED IMAGE
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A QR code is a type of barcode that can hold more information than the familiar kind scanned at checkouts around the world. The “QR” stands for “Quick Response”, a reference to the speed at which the large amounts of information they contain can be decoded by scanners. They are being widely used for advertising campaigns, linking to company websites, contest sign-up pages and online menus. In this paper, we propose an efficient module to extract QR code from background and solve problem of rotation in case of inaccurate image taken from mobile camera.

Publication Date
Sat Apr 30 2022
Journal Name
Iraqi Journal Of Science
Biometric Identification System Based on Contactless Palm-Vein Using Residual Attention Network
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Palm vein recognition technology is a one of the most effective biometric technologies for personal identification. Palm acquisition techniques are either contact-based or contactless-based. The contactless-based palm vein system is considered more accurate and efficient when used in modern applications, but it may suffer from problems like pose variations and the delay in the matching process. This paper proposes a contactless-based identification system for palm vein that involves two main steps; First, the central region of the palm is cropped using fast extract region of interest algorithm, then the features are extracted and classified using altered structure of Residual Attention Network, which is a developed version of convolution

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