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Isolated Word Speech Recognition Using Mixed Transform
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Methods of speech recognition have been the subject of several studies over the past decade. Speech recognition has been one of the most exciting areas of the signal processing. Mixed transform is a useful tool for speech signal processing; it is developed for its abilities of improvement in feature extraction. Speech recognition includes three important stages, preprocessing, feature extraction, and classification. Recognition accuracy is so affected by the features extraction stage; therefore different models of mixed transform for feature extraction were proposed. The properties of the recorded isolated word will be 1-D, which achieve the conversion of each 1-D word into a 2-D form. The second step of the word recognizer requires, the application of 2-D FFT, Radon transform, the 1-D IFFT,and 1-D discrete wavelet transforms were used in the first proposed model, while discrete multicircularlet transform was used in the second proposed model. The final stage of the proposed models includes the use of the dynamic time warping algorithm for recognition tasks. The performance of the proposed systems was evaluated using forty different isolated Arabic words that are recorded fifteen times in a studio for speaker dependant. The result shows recognition accuracy of (91% and 89%) using discrete wavelet transform type Daubechies (Db1) and (Db4) respectively, and the accuracy score between (87%-93%) was achieved using
discrete multicircularlet transform for 9 sub bands.

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Publication Date
Thu Jun 01 2017
Journal Name
Iosr Journal Of Computer Engineering
Lossy Image Compression Using Wavelet Transform, Polynomial Prediction And Block Truncation Coding
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Publication Date
Tue Jun 20 2023
Journal Name
Baghdad Science Journal
Numerical Solutions for the Nonlinear PDEs of Fractional Order by Using a New Double Integral Transform with Variational Iteration Method
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This paper considers a new Double Integral transform called Double Sumudu-Elzaki transform DSET. The combining of the DSET with a semi-analytical method, namely the variational iteration method DSETVIM, to arrive numerical solution of nonlinear PDEs of Fractional Order derivatives. The proposed dual method property decreases the number of calculations required, so combining these two methods leads to calculating the solution's speed. The suggested technique is tested on four problems. The results demonstrated that solving these types of equations using the DSETVIM was more advantageous and efficient

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Publication Date
Mon Dec 31 2018
Journal Name
Iraqi Journal Of Market Research And Consumer Protection
ESTIMATION OF ELLAGIC ACID ACTIVITY WHEN MIXED WITH SOME TYPES OF CANDY AGAINST Streptococcus mutans ISOLATED FROM ADULT PATIENTS IN BAGHDAD CITY: ESTIMATION OF ELLAGIC ACID ACTIVITY WHEN MIXED WITH SOME TYPES OF CANDY AGAINST Streptococcus mutans ISOLATED FROM ADULT PATIENTS IN BAGHDAD CITY
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Microbial activity of Ellagic acid when mixed with some types of candy toward Streptococcus mutans microorganism was studied. The main purpose of carrying out this study is to produce a new type of candy that contains Ellagic acid in addition to xylitol instead of sucrose to prevent dental caries. The results show that the inhibitory action of Ellagic acid was more effective when mixed with this type of candy for the purpose of reducing Streptococcus mutans microorganisms, while sensory evaluation was applied in this study to 20 volunteers to that candy sample evaluated which contain (5 mg/ml) Ellagic acid with 100g xylitol to determine consumers acceptability of this sample of candy. The results were expressed as mean value, slandered d

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Publication Date
Wed May 17 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Extend Differential Transform Methods for Solving Differential Equations with Multiple Delay
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In this paper, we present an approximate analytical and numerical solutions for the differential equations with multiple delay using the extend differential transform method (DTM). This method is used to solve many linear and non linear problems.

 

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Publication Date
Thu Aug 02 2018
Journal Name
Association Of Arab Universities Journal Of Engineering Sciences
Performance Study for Mixed Transforms Generated by Tensor Product in Image Compression and Processing
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In all applications and specially in real time applications, image processing and compression plays in modern life a very important part in both storage and transmission over internet for example, but finding orthogonal matrices as a filter or transform in different sizes is very complex and importance to using in different applications like image processing and communications systems, at present, new method to find orthogonal matrices as transform filter then used for Mixed Transforms Generated by using a technique so-called Tensor Product based for Data Processing, these techniques are developed and utilized. Our aims at this paper are to evaluate and analyze this new mixed technique in Image Compression using the Discrete Wavelet Transfo

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Publication Date
Sun Jan 05 2025
Journal Name
Science Journal Of University Of Zakho
DETECTION AND RECOGNITION OF IRAQI LICENSE PLATES USING CONVOLUTIONAL NEURAL NETWORKS
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Due to the large population of motorway users in the country of Iraq, various approaches have been adopted to manage queues such as implementation of traffic lights, avoidance of illegal parking, amongst others. However, defaulters are recorded daily, hence the need to develop a mean of identifying these defaulters and bring them to book. This article discusses the development of an approach of recognizing Iraqi licence plates such that defaulters of queue management systems are identified. Multiple agencies worldwide have quickly and widely adopted the recognition of a vehicle license plate technology to expand their ability in investigative and security matters. License plate helps detect the vehicle's information automatically ra

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Publication Date
Wed Sep 12 2018
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Recognition of Off-line Printed Arabic Text Using Hidden Markov Models
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In this paper, we introduce a method to identify the text printed in Arabic, since the recognition of the printed text is very important in the applications of information technology, the Arabic language is among a group of languages with related characters such as the language of Urdu , Kurdish language , Persian language also the old Turkish language " Ottoman ", it is difficult to identify the related letter because it is in several cases, such as the beginning of the word has a shape and center of the word has a shape and the last word also has a form, either texts in languages where the characters are not connected, then the image of the letter one in any location in the word has been Adoption of programs ready for him A long time.&

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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
Sat Feb 01 2025
Journal Name
Algorithms
Three-Dimensional Object Recognition Using Orthogonal Polynomials: An Embedded Kernel Approach
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Computer vision seeks to mimic the human visual system and plays an essential role in artificial intelligence. It is based on different signal reprocessing techniques; therefore, developing efficient techniques becomes essential to achieving fast and reliable processing. Various signal preprocessing operations have been used for computer vision, including smoothing techniques, signal analyzing, resizing, sharpening, and enhancement, to reduce reluctant falsifications, segmentation, and image feature improvement. For example, to reduce the noise in a disturbed signal, smoothing kernels can be effectively used. This is achievedby convolving the distributed signal with smoothing kernels. In addition, orthogonal moments (OMs) are a cruc

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Publication Date
Mon Apr 24 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Arabic Characters Recognition by Edge Detection Using Connected Component Contour(CO3)
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  In the present paper, Arabic Character Recognition  Edge detection method based on contour and connected components  is proposed. First stage contour extraction feature is introduced to tackle the Arabic characters edge detection problem, where the aim is to extract the edge information presented in the Arabic characters, since it is crucial to understand the character content.         The second stage connected components appling for the same characters to find edge detection. The proposed approach exploits a number of connected components, which move on the character by character intensity values, to establish matrix, which represents the edge information at each pixel location .

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