Artificial intelligence (AI) is entering many fields of life nowadays. One of these fields is biometric authentication. Palm print recognition is considered a fundamental aspect of biometric identification systems due to the inherent stability, reliability, and uniqueness of palm print features, coupled with their non-invasive nature. In this paper, we develop an approach to identify individuals from palm print image recognition using Orange software in which a hybrid of AI methods: Deep Learning (DL) and traditional Machine Learning (ML) methods are used to enhance the overall performance metrics. The system comprises of three stages: pre-processing, feature extraction, and feature classification or matching. The SqueezeNet deep learning model was utilized to resize images and feature extraction. Finally, different ML classifiers have been tested for recognition based on the extracted features. The effectiveness of each classifier was assessed using various performance metrics. The results show that the proposed system works well, and all the methods achieved good results; however, the best results obtained were for the Support Vector Machine (SVM) with a linear kernel.
TV medium derives its formal shape from the technological development taking place in all scientific fields, which are creatively fused in the image of the television, which consists mainly of various visual levels and formations. But by the new decade of the second millennium, the television medium and mainly (drama) became looking for that paradigm shift in the aesthetic formal innovative fields and the advanced expressive performative fields that enable it to develop in treating what was impossible to visualize previously. In the meantime, presenting what is new and innovative in the field of unprecedented and even the familiar objective and intellectual treatments. Thus the TV medium has sought for work
... Show MoreIn this paper, we describe a new method for image denoising. We analyze properties of the Multiwavelet coefficients of natural images. Also it suggests a method for computing the Multiwavelet transform using the 1st order approximation. This paper describes a simple and effective model for noise removal through suggesting a new technique for retrieving the image by allowing us to estimate it from the noisy image. The proposed algorithm depends on mixing both soft-thresholds with Mean filter and applying concurrently on noisy image by dividing into blocks of equal size (for concurrent processed to increase the performance of the enhancement process and to decease the time that is needed for implementation by applying the proposed algorith
... Show MoreThe digital multimedia systems become standard at this time because of their extremely sensory activity effects and also the advanced development in its corresponding technology. Recently, biological techniques applied to several varieties of applications such as authentication protocols, organic chemistry, and cryptography. Deoxyribonucleic Acid (DNA) is a tool to hide the key information in multimedia platforms.
In this paper, an embedding algorithm is introduced; first, the image is divided into equally sized blocks, these blocks checked for a small amount color in all the separated blocks. The selected blocks are used to localize the necessary image information. In the second stage, a comparison is between the initial image pixel
Developing a new adaptive satellite images classification technique, based on a new way of merging between regression line of best fit and new empirical conditions methods. They are supervised methods to recognize different land cover types on Al habbinya region. These methods should be stand on physical ground that represents the reflection of land surface features. The first method has separated the arid lands and plants. Empirical thresholds of different TM combination bands; TM3, TM4, and TM5 were studied in the second method, to detect and separate water regions (shallow, bottomless, and very bottomless). The Optimum Index Factor (OIF) is computed for these combination bands, which realized
... Show MoreAbstract
Metal cutting processes still represent the largest class of manufacturing operations. Turning is the most commonly employed material removal process. This research focuses on analysis of the thermal field of the oblique machining process. Finite element method (FEM) software DEFORM 3D V10.2 was used together with experimental work carried out using infrared image equipment, which include both hardware and software simulations. The thermal experiments are conducted with AA6063-T6, using different tool obliquity, cutting speeds and feed rates. The results show that the temperature relatively decreased when tool obliquity increases at different cutting speeds and feed rates, also it
... Show MoreIn this paper, the goal of proposed method is to protect data against different types of attacks by unauthorized parties. The basic idea of proposed method is generating a private key from a specific features of digital color image such as color (Red, Green and Blue); the generating process of private key from colors of digital color image performed via the computing process of color frequencies for blue color of an image then computing the maximum frequency of blue color, multiplying it by its number and adding process will performed to produce a generated key. After that the private key is generated, must be converting it into the binary representation form. The generated key is extracted from blue color of keyed image then we selects a c
... Show MoreThe present study examines critically the discursive representation of Arab immigrants in selected American news channels. To achieve the aim of this study, twenty news subtitles have been exacted from ABC and NBC channels. The selected news subtitles have been analyzed within van Dijk’s (2000) critical discourse analysis framework. Ten discourse categories have been examined to uncover the image of Arab immigrants in the American news channels. The image of Arab immigrants has been examined in terms of five ideological assumptions including "us vs. them", "ingroup vs. outgroup", "victims vs. agents", "positive self-presentation vs. negative other-presentation", and "threat vs. non-threat". Analysis of data reveals that Arab immig
... Show MoreImage compression plays an important role in reducing the size and storage of data while increasing the speed of its transmission through the Internet significantly. Image compression is an important research topic for several decades and recently, with the great successes achieved by deep learning in many areas of image processing, especially image compression, and its use is increasing Gradually in the field of image compression. The deep learning neural network has also achieved great success in the field of processing and compressing various images of different sizes. In this paper, we present a structure for image compression based on the use of a Convolutional AutoEncoder (CAE) for deep learning, inspired by the diversity of human eye
... Show MoreThis study aims to observe and analysis the propaganda discourse image for Daesh, and know how it marketing the fear due to symbols structure, and discover the straight meanings and hidden inspiration, with the ideology that the image presented.
The study is descriptive and qualitative, and the method is analytic survey used semiotic approach.
The most important results of the study refer to:
- Daesh functioning the image in fear manufacture in all it components: the symbol of savageness, body language, color, clothes uniform and professionally shot.
- The indicative meaning of fear promoted by Daesh based of the manufacturing «Holy», and that mean places non-touchable and non-insulted.
- Daesh used in its propagand