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Image Steganography using Dynamic Threshold based on Discrete Cosine Transform
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The art of preventing the detection of hidden information messages is the way that steganography work. Several algorithms have been proposed for steganographic techniques. A major portion of these algorithms is specified for image steganography because the image has a high level of redundancy. This paper proposed an image steganography technique using a dynamic threshold produced by the discrete cosine coefficient. After dividing the green and blue channel of the cover image into 1*3-pixel blocks, check if any bits of green channel block less or equal to threshold then start to store the secret bits in blue channel block, and to increase the security not all bits in the chosen block used to store the secret bits. Firstly, store in the center of the block and then store another bit in the write or left bit depended on differences between them. The proposed method was applied to many color images and many measurement terms used to show the efficiency of it. The experiment result showed good result that the PSNR = 53.76, MSE = 0.273, SSIM= 0.999, with embedding rates 0.55.

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Publication Date
Thu Aug 02 2012
Journal Name
International Journal Of Advanced Research In Computer Science
User Authentication based on Keystroke Dynamics Using Backpropagation Network
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Computer systems and networks are being used in almost every aspect of our daily life; as a result the security threats to computers and networks have also increased significantly. Traditionally, password-based user authentication is widely used to authenticate legitimate user in the current system0T but0T this method has many loop holes such as password sharing, shoulder surfing, brute force attack, dictionary attack, guessing, phishing and many more. The aim of this paper is to enhance the password authentication method by presenting a keystroke dynamics with back propagation neural network as a transparent layer of user authentication. Keystroke Dynamics is one of the famous and inexpensive behavioral biometric technologies, which identi

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Publication Date
Fri Nov 01 2019
Journal Name
International Journal Of Computer Science And Mobile Computing
Adaptive Color Image Compression of Hybrid Coding and Inter Differentiation Based Techniques
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Publication Date
Tue Mar 25 2014
Journal Name
Sensors
Minimal Camera Networks for 3D Image Based Modeling of Cultural Heritage Objects
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Publication Date
Mon Nov 21 2022
Journal Name
Sensors
Deep Learning-Based Computer-Aided Diagnosis (CAD): Applications for Medical Image Datasets
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Computer-aided diagnosis (CAD) has proved to be an effective and accurate method for diagnostic prediction over the years. This article focuses on the development of an automated CAD system with the intent to perform diagnosis as accurately as possible. Deep learning methods have been able to produce impressive results on medical image datasets. This study employs deep learning methods in conjunction with meta-heuristic algorithms and supervised machine-learning algorithms to perform an accurate diagnosis. Pre-trained convolutional neural networks (CNNs) or auto-encoder are used for feature extraction, whereas feature selection is performed using an ant colony optimization (ACO) algorithm. Ant colony optimization helps to search for the bes

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Publication Date
Thu Sep 01 2022
Journal Name
Jordan Journal Of Mechanical And Industrial Engineering
Empact of Discrete Multi-arc Rib Roughness on the Effective Efficiency of a Solar Air Heater
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Artificial roughness on the absorber plate of a Solar Air Heater (SAH) is a popular technique for increasing its effective efficiency. The study investigated the effect of geometrical parameters of discrete multi-arc ribs (DMAR) installed below the SAH absorber plate on the effective efficiency. The effects of major roughness factors, such as number of gaps (Ng = 1-4), rib pitch (p/e = 4-16), rib height (e/D = 0.018-0.045), gab width (wg/e = 0.5-2), angle of attack ( = 30-75), and Reynolds number (Re= 2000-20000) on the performance of a SAH are studied. The performance of the SAH is evaluated using a top-down iterative technique. The results show that as Re rises, SAH-effective DMAR's efficiency first ascends to a specified value o

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Publication Date
Mon Dec 03 2012
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
The Effect of Window Size Changing on Satellite Image Segmentation Using 2D Fast Otsu Method
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Publication Date
Wed Jun 10 2009
Journal Name
Iraqi Journal Of Laser
Characteristic of Discrete Raman Amplifier at Different Pump Configurations
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Discrete Raman amplifier have many attractive aspects over rare-earth doped fiber amplifier such as (EDFA) including arbitrary gain band, better adjustability of gain shape, and better linearity. This paper shows that discrete Raman amplifier has higher gain in bidirectional pumping than counter pumping. The gain increases with increasing fiber length, and the noise figure remain at the same value for short fiber length.

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Publication Date
Fri Sep 09 2022
Journal Name
Research Anthology On Improving Medical Imaging Techniques For Analysis And Intervention
Groupwise Non-Rigid Image Alignment Using Few Parameters
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Groupwise non-rigid image alignment is a difficult non-linear optimization problem involving many parameters and often large datasets. Previous methods have explored various metrics and optimization strategies. Good results have been previously achieved with simple metrics, requiring complex optimization, often with many unintuitive parameters that require careful tuning for each dataset. In this chapter, the problem is restructured to use a simpler, iterative optimization algorithm, with very few free parameters. The warps are refined using an iterative Levenberg-Marquardt minimization to the mean, based on updating the locations of a small number of points and incorporating a stiffness constraint. This optimization approach is eff

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Publication Date
Sun Feb 24 2019
Journal Name
Iraqi Journal Of Physics
Adaptive inter frame compression using image segmented technique
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The computer vision branch of the artificial intelligence field is concerned with developing algorithms for analyzing video image content. Extracting edge information, which is the essential process in most pictorial pattern recognition problems. A new method of edge detection technique has been introduces in this research, for detecting boundaries.

           Selection of typical lossy techniques for encoding edge video images are also discussed in this research. The concentration is devoted to discuss the Block-Truncation coding technique and Discrete Cosine Transform (DCT) coding technique. In order to reduce the volume of pictorial data which one may need to store or transmit,

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Publication Date
Fri Jun 01 2018
Journal Name
Journal Of Physics: Conference Series
Hiding text in gray image using mapping technique
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