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A Recognition System for Subjects' Signature Using the Spatial Distribution of Signature Body
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This investigation proposed an identification system of offline signature by utilizing rotation compensation depending on the features that were saved in the database. The proposed system contains five principle stages, they are: (1) data acquisition, (2) signature data file loading, (3) signature preprocessing, (4) feature extraction, and (5) feature matching. The feature extraction includes determination of the center point coordinates, and the angle for rotation compensation (θ), implementation of rotation compensation, determination of discriminating features and statistical condition. During this work seven essential collections of features are utilized to acquire the characteristics: (i) density (D), (ii) average (A), (iii) standard deviation (S) and integrated between them (iv) density and average (DA), (v) density and standard deviation (DS), (vi) average and standard deviation (AS), and finally (vii) density with average and standard deviation (DAS). The determined values of features are assembled in a feature vector used to distinguish signatures belonging to different persons. The utilized two Euclidean distance measures for matching stage are: (i) normalized mean absolute distance (nMAD) (ii) normalized mean squared distance (nMSD). The suggested system is tested by a public dataset collect from 612 images of handwritten signatures. The best recognition rate (i.e., 98.9%) is achieved in the proposed system using number of blocks (21×21) in density feature set. With the same number of blocks (i.e., 21×21) the maximum verification accuracy obtained is (100%).

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Publication Date
Sat Sep 30 2023
Journal Name
Wasit Journal Of Computer And Mathematics Science
Real time handwriting recognition system using CNN algorithms
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Abstract— The growing use of digital technologies across various sectors and daily activities has made handwriting recognition a popular research topic. Despite the continued relevance of handwriting, people still require the conversion of handwritten copies into digital versions that can be stored and shared digitally. Handwriting recognition involves the computer's strength to identify and understand legible handwriting input data from various sources, including document, photo-graphs and others. Handwriting recognition pose a complexity challenge due to the diversity in handwriting styles among different individuals especially in real time applications. In this paper, an automatic system was designed to handwriting recognition

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Publication Date
Thu Jan 13 2022
Journal Name
Medical & Biological Engineering & Computing
An integrated entropy-spatial framework for automatic gender recognition enhancement of emotion-based EEGs
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Publication Date
Wed Jan 01 2020
Journal Name
Ieee Transactions On Computers
Neuromorphic System for Spatial and Temporal Information Processing
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Publication Date
Fri Sep 30 2022
Journal Name
Iraqi Journal Of Science
A Deep Study on the Performance of the Spatial Density Distribution Method to Recognize Handwritten Signatures
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    A signature is a special identifier that confirms a person's identity and distinguishes him or her from others. The main goal of this paper is to present a deep study of the spatial density distribution method and the effect of a mass-based segmentation algorithm on its performance while it is being used to recognize handwritten signatures in an offline mode. The methodology of the algorithm is based on dividing the image of the signature into tiles that reflect the shape and geometry of the signature, and then extracting five spatial features from each of these tiles. Features include the mass of each tile, the relative mean, and the relative standard deviation for the vertical and horizontal projections of that tile. In the clas

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Publication Date
Sun Oct 29 2023
Journal Name
Journal Of Al-qadisiyah For Computer Science And Mathematics
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 wa

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Publication Date
Sun Apr 30 2023
Journal Name
Iraqi Journal Of Science
Automatic Numeral Recognition System Using Local Statistical and Geometrical Features
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     Optical Character Recognition (OCR) research includes computer vision, artificial intelligence, and pattern recognition. Character recognition has garnered a lot of attention in the last decade due to its broad variety of uses and applications, including multiple-choice test data, business documents (e.g., ID cards, bank notes, passports, etc.), and automatic number plate recognition. This paper introduces an automatic recognition system for printed numerals. The automatic reading system is based on extracting local statistical and geometrical features from the text image. Those features are represented by eight vectors extracted from each digit. Two of these features are local statistical (A, A th), and six are local

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Publication Date
Sat Apr 01 2023
Journal Name
Iop Conference Series: Earth And Environmental Science
Spatial Distribution of Soil Quality and Health Index for the Umm Al-Naaj Marsh in Maysan
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The Umm Al-Naaj Marsh was chosen in Maysan province, and it is one of the sections of Mar Al-Hawza, which is one of the most prominent Iraqi marshes in the south. The marshes are located between latitudes 30 35 and 32 45 latitudes and longitudes 13 46 and 48 00. The area of the study area is 76479.432142 hectares to evaluate soil quality and health index and their spatial distribution based on measuring physical, chemical, biological and fertility traits and calculating the total quality index for those characteristics. Using an auger drilling machine, we collected 50 randomly selected surface samples, evenly distributed across the study region, from Al-Aq 0.0–0.30 m, noting their precise locations along the way. Soil health and quality w

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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
Tue Sep 08 2020
Journal Name
Baghdad Science Journal
Improved throughput of Elliptic Curve Digital Signature Algorithm (ECDSA) processor implementation over Koblitz curve k-163 on Field Programmable Gate Array (FPGA)
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            The widespread use of the Internet of things (IoT) in different aspects of an individual’s life like banking, wireless intelligent devices and smartphones has led to new security and performance challenges under restricted resources. The Elliptic Curve Digital Signature Algorithm (ECDSA) is the most suitable choice for the environments due to the smaller size of the encryption key and changeable security related parameters. However, major performance metrics such as area, power, latency and throughput are still customisable and based on the design requirements of the device.

The present paper puts forward an enhancement for the throughput performance metric by p

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Publication Date
Sun Mar 01 2020
Journal Name
Iop Conference Series: Materials Science And Engineering
Using spatial analysis techniques to Preparing maps for distribution of pollutant concentrations in Shatt al-Arab waters in November 2015
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Abstract<p>Water has a great self-generating capacity that can neutralize the polluting interventions carried out by humans. However, if human activities continue this uncontrolled and unsustainable exploitation of this resource, this regenerating capacity shall fail and it will be jeopardized definitively. Shatt Al-Arab River in South of Iraq. It has an active role in providing water for irrigation, industry, domestic use and a commercial gateway to Iraq. in the last five years Shatt Al-Arab suffered from a rise in pollutants due to the severe decline in sewage networks, irregular networks and pesticide products, as well as the outputs of factories and companies that find their way to water sou</p> ... Show More
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