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Secure Image Steganography using Biorthogonal Wavelet Transform
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Publication Date
Mon Sep 25 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Analyzing Laser Speckle Pattern Using the Discrete Cosine Transform
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The use of Cosine transform to analyze the model-noise pattern alteration with different vibration model applied on multimode fiber optics are studied. It's results compared with the Fourier transform to perform the same analysis using total frequency difference and the computation time, which almost coincide for the both transforms. A discussion for the results and recommendation are introduced.

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Publication Date
Sun Aug 01 2021
Journal Name
Journal Of Physics: Conference Series
EEG Motor-Imagery BCI System Based on Maximum Overlap Discrete Wavelet Transform (MODWT) and cubic SVM
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Abstract<p>Communication of the human brain with the surroundings became reality by using Brain- Computer Interface (BCI) based mechanism. Electroencephalography (EEG) being the non-invasive method has become popular for interaction with the brain. Traditionally, the devices were used for clinical applications to detect various brain diseases but with the advancement in technologies, companies like Emotiv, NeuoSky are coming up with low cost, easily portable EEG based consumer graded devices that can be used in various application domains like gaming, education etc as these devices are comfortable to wear also. This paper reviews the fields where the EEG has shown its impact and the way it has p</p> ... Show More
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Publication Date
Fri Jun 24 2022
Journal Name
Iraqi Journal Of Science
Steganography Based on Arabic Language Texts by Kashida Using STRI As RNG
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One of the primary problems in internet is security, mostly when computer utilization is increasing in all social and business areas. So, the secret communications through public and private channels are the major goal of researchers. Information hiding is one of methods to obtain a security communication medium and protecting the data during transmission.
This research offers in a new method using two levels to hide, the first level is hiding by embedding and addition but the second level is hiding by injection. The first level embeds a secret message in one bit in the LSB in the FFT and the addition of one kashida. Subtraction of two random images (STRI) is RNG to find positions for hiding within the text. The second level is the in

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Publication Date
Mon Dec 31 2012
Journal Name
Al-khwarizmi Engineering Journal
Speech Compression Using Multecirculerletet Transform
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Compressing the speech reduces the data storage requirements, leading to reducing the time of transmitting the digitized speech over long-haul links like internet. To obtain best performance in speech compression, wavelet transforms require filters that combine a number of desirable properties, such as orthogonality and symmetry.The MCT bases functions are derived from GHM bases function using 2D linear convolution .The fast computation algorithm methods introduced here added desirable features to the current transform. We further assess the performance of the MCT in speech compression application. This paper discusses the effect of using DWT and MCT (one and two dimension) on speech compression. DWT and MCT performances in terms of comp

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Publication Date
Mon Dec 06 2021
Journal Name
Iraqi Journal Of Science
Images Compression Using Bezier curve with Ridgelet Transform
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The data compression is a very important process in order to reduce the size of a large data to be stored or transported, parametric curves such that Bezier curve is a suitable method to return gradual change and mutability of this data. Ridghelet transform solve the problems in the wavelet transform and it can compress the image well but when it uses with Bezier curve, the equality of compressed image become very well. In this paper, a new compression method is proposed by using Bezier curve with Ridgelet transform on RGB images. The results showed that the proposed method present good performance in both subjective and objective experiments. When the PSNR values equal to (34.2365, 33.4323 and 33.0987), they were increased in the propos

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Publication Date
Tue Feb 01 2022
Journal Name
Baghdad Science Journal
Securing Text Messages Using Graph Theory and Steganography
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      Data security is an important component of data communication and transmission systems. Its main role is to keep sensitive information safe and integrated from the sender to the receiver. The proposed system aims to secure text messages through two security principles encryption and steganography. The system produced a novel method for encryption using graph theory properties; it formed a graph from a password to generate an encryption key as a weight matrix of that graph and invested the Least Significant Bit (LSB) method for hiding the encrypted message in a colored image within a green component. Practical experiments of (perceptibility, capacity, and robustness) were calculated using similarity measures like PSNR, MSE, and

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Scopus (9)
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Publication Date
Fri Jul 30 2021
Journal Name
Iraqi Journal For Electrical And Electronic Engineering
EEG Motor-Imagery BCI System Based on Maximum Overlap Discrete Wavelet Transform (MODWT) and Machine learning algorithm
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The ability of the human brain to communicate with its environment has become a reality through the use of a Brain-Computer Interface (BCI)-based mechanism. Electroencephalography (EEG) has gained popularity as a non-invasive way of brain connection. Traditionally, the devices were used in clinical settings to detect various brain diseases. However, as technology advances, companies such as Emotiv and NeuroSky are developing low-cost, easily portable EEG-based consumer-grade devices that can be used in various application domains such as gaming, education. This article discusses the parts in which the EEG has been applied and how it has proven beneficial for those with severe motor disorders, rehabilitation, and as a form of communi

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Publication Date
Tue Nov 30 2021
Journal Name
Iraqi Journal Of Science
Text-based Steganography using Huffman Compression and AES Encryption Algorithm
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In every system of security, to keep important data confidential, we need a high degree of protection. Steganography can be defined as a way of sending confidential texts through a secure medium of communications as well as protecting the information during the process of transmission. Steganography is a technology that is used to protect users' security and privacy. Communication is majorly achieved using a network through SMS, e-mail, and so on. The presented work suggested a technology of text hiding for protecting secret texts with Unicode characters. The similarities of glyphs  provided invisibility and increased the hiding capacity. In conclusion, the proposed method succeeded in securing confidential data and achieving high p

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Scopus (4)
Crossref (3)
Scopus Crossref
Publication Date
Sun Apr 23 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Proposed Speech Analyses Method Using the Multiwavelet Transform
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  Speech is the first invented way of communication that human used age before the invention of writing. In this paper, proposed method for speech analyses to extract features by using multiwavelet Transform (Repeated Row Preprocessing).The proposed system depends on the Euclidian differences of the coefficients of the multiwavelet Transform to determine the beast features of speech recognition. Each sample value in the reference file is computed by taking the average value of four samples for the same data (four speakers for the same phoneme). The result of the input data to every frame value in the reference file using the Euclidian distance to determine the frame with the minimum distance is said to be the "Best Match". Simulatio

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Publication Date
Fri Jun 24 2022
Journal Name
Iraqi Journal Of Science
Feature Extraction of Human Facail Expressions Using Haar Wavelet and Neural network
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One of the challenging and active research topics in the recent years is Facial Expression. This paper presents the method to extract the features from the facial expressions from still images. Feature extraction is very important for classification and recognition process. This paper involve three stages which contain capture the images, pre-processing and feature extractions. This method is very efficient in feature extraction by applying haar wavelet and Karhunen-Loève Transform (KL-T). The database used in this research is from Cohen-Kanade which used six expressions of anger, sadness fear, happiness, disgust and surprise. Features that have been extracted from the image of facial expressions were used as inputs to the neural networ

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