Researchers are increasingly using multimodal biometrics to strengthen the security of biometric applications. In this study, a strong multimodal human identification model was developed to address the growing problem of spoofing attacks in biometric security systems. Through the use of metaheuristic optimization methods, such as the Genetic Algorithm(GA), Ant Colony Optimization(ACO), and Particle Swarm Optimization (PSO) for feature selection, this unique model incorporates three biometric modalities: face, iris, and fingerprint. Image pre-processing, feature extraction, critical image feature selection, and multibiometric recognition are the four main steps in the workflow of the system. To determine its performance, the model was evaluated on the SDUMLA-HMT dataset, which contains a variety of biometric features from various individuals. The system outperformed existing techniques in the literature with an excellent recognition accuracy of 99.4%. Although this result is encouraging, further research on larger and more varied datasets is necessary to confirm its applicability across many circumstances. This study highlights how multimodal biometrics strengthened by metaheuristic algorithms can considerably increase biometric security against spoofing assaults, thereby opening a promising new direction for future development in the field.
In the image processing’s field and computer vision it’s important to represent the image by its information. Image information comes from the image’s features that extracted from it using feature detection/extraction techniques and features description. Features in computer vision define informative data. For human eye its perfect to extract information from raw image, but computer cannot recognize image information. This is why various feature extraction techniques have been presented and progressed rapidly. This paper presents a general overview of the feature extraction categories for image.
A watermark is a pattern or image defined in a paper that seems as different shades of light/darkness when viewed by the transmitted light which used for improving the robustness and security. There are many ways to work Watermark, including the addition of an image or text to the original image, but in this paper was proposed another type of watermark is add curves, line or forms have been drawn by interpolation, which produces watermark difficult to falsify and manipulate it. Our work suggests new techniques of watermark images which is embedding Cubic-spline interpolation inside the image using Bit Plane Slicing. The Peak to Signal Noise Ratio (PSNR) and Mean Square Error (MSE) value is calculated so that the quality of the original i
... Show MoreThe theatrical show consists of theatrical techniques that form the space to display the play that may form conscious visual effects about the receiver. The current search included the (Research problem) which is the immediate question ((What makes the theatrical techniques dazzling and visually exciting in a certain theatrical show?))
It also included (the importance of research) by highlighting the importance of theatrical techniques and the mechanism of contrast.
It also identified the visual stimulus of theatrical techniques in the theater show.
It also included the (research limits), which were temporally determined by the period (1990-1998) and spatially, the Iraqi theater shows (Baghdad), in which theatrical techniques c
The recent advancements in security approaches have significantly increased the ability to identify and mitigate any type of threat or attack in any network infrastructure, such as a software-defined network (SDN), and protect the internet security architecture against a variety of threats or attacks. Machine learning (ML) and deep learning (DL) are among the most popular techniques for preventing distributed denial-of-service (DDoS) attacks on any kind of network. The objective of this systematic review is to identify, evaluate, and discuss new efforts on ML/DL-based DDoS attack detection strategies in SDN networks. To reach our objective, we conducted a systematic review in which we looked for publications that used ML/DL approach
... Show MoreTo date, comprehensive reviews and discussions of the strengths and limitations of Remote Sensing (RS) standalone and combination approaches, and Deep Learning (DL)-based RS datasets in archaeology have been limited. The objective of this paper is, therefore, to review and critically discuss existing studies that have applied these advanced approaches in archaeology, with a specific focus on digital preservation and object detection. RS standalone approaches including range-based and image-based modelling (e.g., laser scanning and SfM photogrammetry) have several disadvantages in terms of spatial resolution, penetrations, textures, colours, and accuracy. These limitations have led some archaeological studies to fuse/integrate multip
... Show MoreThis study focused on the role and importance of alkaloid compounds in Punica granatum peels which is one of many wide distribution medicinal fruits. Two kinds of pathogenic fungi were isolated from patients in Baghdad to be tested, also a type of extracts was prepared, alkaloids were isolated and partially purified and detected by two ways, a classic depended technique also used for determine these alkaloids, results showed an observed differences among extracts or treatments towards the fungi samples. So this study was one of the scientific applications to find natural alternative compounds that inhibit the growth of several pathogenic organisms that cause dangers and harms for human health.
The research aims to apply one of the techniques of management accounting, which is the Quality Function Deployment(QFD) on the Pepsi product in Baghdad Soft Drinks Company and to determine the technical requirements objectively that have been applied in practice in Baghdad Soft Drinks Company / a private shareholding company, as it focuses on meeting the quality requirements and achieving positive quality to provide a product It meets the requirements of current and future customers, hence the importance of research that indicates that the Quality Function Deployment(QFD) is a useful tool to develop the requirements of new products, being a design process driven by customers through their voices, and thus contribute to achieve a competi
... Show MoreThe work in this paper involves the planning, design and implementation of a mobile learning system called Nahrain Mobile Learning System (NMLS). This system provides complete teaching resources, which can be accessed by the students, instructors and administrators through the mobile phones. It presents a viable alternative to Electronic learning. It focuses on the mobility and flexibility of the learning practice, and emphasizes the interaction between the learner and learning content. System users are categorized into three categories: administrators, instructors and students. Different learning activities can be carried out throughout the system, offering necessary communication tools to allow the users to communicate with each other
... Show MoreThe diagnoses system of varicose disease has a good level of performance due to the complexity and uniqueness in patterns of vein of the leg. In addition, the patterns of vein are internal of the body, and its features are hard to duplicate, this reason make this method not easy to fake, and thus make it contains of a good features for varicose disease diagnoses. The proposed system used more than one type of algorithms to produce diagnoses system of varicose disease with high accuracy, in addition, this multi-algorithm technique based on veins as a factor to recognize varicose infection. The obtained results indicate that the design of varicose diagnoses system by applying multi- algorithms (Naïve Bayes and Back-Propagation) produced new
... Show MoreRecommendation systems are now being used to address the problem of excess information in several sectors such as entertainment, social networking, and e-commerce. Although conventional methods to recommendation systems have achieved significant success in providing item suggestions, they still face many challenges, including the cold start problem and data sparsity. Numerous recommendation models have been created in order to address these difficulties. Nevertheless, including user or item-specific information has the potential to enhance the performance of recommendations. The ConvFM model is a novel convolutional neural network architecture that combines the capabilities of deep learning for feature extraction with the effectiveness o
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