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Offline signatures matching using haar wavelet subbands
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The complexity of multimedia contents is significantly increasing in the current world. This leads to an exigent demand for developing highly effective systems to satisfy human needs. Until today, handwritten signature considered an important means that is used in banks and businesses to evidence identity, so there are many works tried to develop a method for recognition purpose. This paper introduced an efficient technique for offline signature recognition depending on extracting the local feature by utilizing the haar wavelet subbands and energy. Three different sets of features are utilized by partitioning the signature image into non overlapping blocks where different block sizes are used. CEDAR signature database is used as a dataset for testing purpose. The results achieved by this technique indicate a high performance in signature recognition.

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Publication Date
Sun Sep 30 2018
Journal Name
Journal Of Theoretical And Applied Information Technology
FINGERPRINTS MATCHING USING THE ENERGY AND LOW ORDER MOMENT OF HAAR WAVELET SUBBANDS
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Fingerprint recognition is one among oldest procedures of identification. An important step in automatic fingerprint matching is to mechanically and dependably extract features. The quality of the input fingerprint image has a major impact on the performance of a feature extraction algorithm. The target of this paper is to present a fingerprint recognition technique that utilizes local features for fingerprint representation and matching. The adopted local features have determined: (i) the energy of Haar wavelet subbands, (ii) the normalized of Haar wavelet subbands. Experiments have been made on three completely different sets of features which are used when partitioning the fingerprint into overlapped blocks. Experiments are conducted on

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Publication Date
Sat Sep 09 2017
Journal Name
International Journal Of Science And Research (ijsr)
Fingerprints Recognition Using the Local Energy Distribution over Haar Wavelet Subbands
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Fingerprints are commonly utilized as a key technique and for personal recognition and in identification systems for personal security affairs. The most widely used fingerprint systems utilizing the distribution of minutiae points for fingerprint matching and representation. These techniques become unsuccessful when partial fingerprint images are capture, or the finger ridges suffer from lot of cuts or injuries or skin sickness. This paper suggests a fingerprint recognition technique which utilizes the local features for fingerprint representation and matching. The adopted local features have determined using Haar wavelet subbands. The system was tested experimentally using FVC2004 databases, which consists of four datasets, each set holds

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Publication Date
Tue Jun 01 2021
Journal Name
Telkomnika (telecommunication Computing Electronics And Control)
An efficient method for stamps recognition using Haar wavelet sub-bands
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Publication Date
Sun Jul 01 2012
Journal Name
Baghdad University College Of Education Ibn Al-haitham
Numerical Solution of Linear System of Fredholm Integral Equations Using Haar Wavelet Method
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The aim of this paper is to present the numerical method for solving linear system of Fredholm integral equations, based on the Haar wavelet approach. Many test problems, for which the exact solution is known, are considered. Compare the results of suggested method with the results of another method (Trapezoidal method). Algorithm and program is written by Matlab vergion 7.

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Publication Date
Wed Apr 28 2021
Journal Name
2021 1st Babylon International Conference On Information Technology And Science (bicits)
An Efficient Method for Stamps Verification Using Haar Wavelet Sub-bands with Histogram and Moment
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Publication Date
Fri Dec 29 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Panchromatic and Multispectral Image Fusion by Combining IHS Transform and Haar Wavelet
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The technique of integrate complimentary details from two or more input images is known as image fusion.  The fusion image is more informational and will be complete more than any of the original input images. This paper Illustrates implementation and evaluation of fusion techniques used on the Satellite images a high-resolution Panchromatic (Pan) and Multispectral (MS). A new algorithm is proposed to fuse a  Pan  and MS  of the lowresolution images based on combining IHS and Haar wavelet transform.Firstly, this paper clarifies the classical fusion by using IHS transform and Haar wavelet transform individually. Secondly proposition new strategy of combining the two methods. Performance of the proposed method is evalua

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Publication Date
Sat Oct 01 2022
Journal Name
Baghdad Science Journal
Offline Signature Biometric Verification with Length Normalization using Convolution Neural Network
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Offline handwritten signature is a type of behavioral biometric-based on an image. Its problem is the accuracy of the verification because once an individual signs, he/she seldom signs the same signature. This is referred to as intra-user variability. This research aims to improve the recognition accuracy of the offline signature. The proposed method is presented by using both signature length normalization and histogram orientation gradient (HOG) for the reason of accuracy improving. In terms of verification, a deep-learning technique using a convolution neural network (CNN) is exploited for building the reference model for a future prediction. Experiments are conducted by utilizing 4,000 genuine as well as 2,000 skilled forged signatu

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Publication Date
Sat Aug 03 2024
Journal Name
Proceedings Of Ninth International Congress On Information And Communication Technology
Offline Signature Verification Based on Neural Network
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The investigation of signature validation is crucial to the field of personal authenticity. The biometrics-based system has been developed to support some information security features.Aperson’s signature, an essential biometric trait of a human being, can be used to verify their identification. In this study, a mechanism for automatically verifying signatures has been suggested. The offline properties of handwritten signatures are highlighted in this study which aims to verify the authenticity of handwritten signatures whether they are real or forged using computer-based machine learning techniques. The main goal of developing such systems is to verify people through the validity of their signatures. In this research, images of a group o

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Publication Date
Tue Feb 01 2022
Journal Name
Baghdad Science Journal
Numerical Solution for Linear State Space Systems using Haar Wavelets Method
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In this research, Haar wavelets method has been utilized to approximate a numerical solution for Linear state space systems. The solution technique is used Haar wavelet functions and Haar wavelet operational matrix with the operation to transform the state space system into a system of linear algebraic equations which can be resolved by MATLAB over an interval from 0 to . The exactness of the state variables can be enhanced by increasing the Haar wavelet resolution. The method has been applied for different examples and the simulation results have been illustrated in graphics and compared with the exact solution.

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Publication Date
Thu Feb 25 2016
Journal Name
Research Journal Of Applied Sciences, Engineering And Technology
Block Matching Algorithm Using Mean and Low Order Moments
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In this study, a fast block matching search algorithm based on blocks' descriptors and multilevel blocks filtering is introduced. The used descriptors are the mean and a set of centralized low order moments. Hierarchal filtering and MAE similarity measure were adopted to nominate the best similar blocks lay within the pool of neighbor blocks. As next step to blocks nomination the similarity of the mean and moments is used to classify the nominated blocks and put them in one of three sub-pools, each one represents certain nomination priority level (i.e., most, less & least level). The main reason of the introducing nomination and classification steps is a significant reduction in the number of matching instances of the pixels belong to the c

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