Due to advancements in computer science and technology, impersonation has become more common. Today, biometrics technology is widely used in various aspects of people's lives. Iris recognition, known for its high accuracy and speed, is a significant and challenging field of study. As a result, iris recognition technology and biometric systems are utilized for security in numerous applications, including human-computer interaction and surveillance systems. It is crucial to develop advanced models to combat impersonation crimes. This study proposes sophisticated artificial intelligence models with high accuracy and speed to eliminate these crimes. The models use linear discriminant analysis (LDA) for feature extraction and mutual information (MI), along with analysis of variance (ANOVA) for feature selection. Two iris classification systems were developed: one using LDA as an input for the OneR machine learning algorithm and another innovative hybrid model based on a One Dimensional Convolutional Neural Network (HM-1DCNN). The MMU database was employed, achieving a performance measure of 94.387% accuracy for the OneR model. Additionally, the HM-1DCNN model achieved 99.9% accuracy by integrating LDA with MI and ANOVA. Comparisons with previous studies show that the HM-1DCNN model performs exceptionally well, with at least 1.69% higher accuracy and lower processing time.
There is various human biometrics used nowadays, one of the most important of these biometrics is the face. Many techniques have been suggested for face recognition, but they still face a variety of challenges for recognizing faces in images captured in the uncontrolled environment, and for real-life applications. Some of these challenges are pose variation, occlusion, facial expression, illumination, bad lighting, and image quality. New techniques are updating continuously. In this paper, the singular value decomposition is used to extract the features matrix for face recognition and classification. The input color image is converted into a grayscale image and then transformed into a local ternary pattern before splitting the image into
... Show More—Medical images have recently played a significant role in the diagnosis and detection of various diseases. Medical imaging can provide a means of direct visualization to observe through the human body and notice the small anatomical change and biological processes associated by different biological and physical parameters. To achieve a more accurate and reliable diagnosis, nowadays, varieties of computer aided detection (CAD) and computer-aided diagnosis (CADx) approaches have been established to help interpretation of the medical images. The CAD has become among the many major research subjects in diagnostic radiology and medical imaging. In this work we study the improvement in accuracy of detection of CAD system when comb
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Nowadays, the adoption of economic unity on the accuracy of financial reporting is very important. Economic units need accurate financial reporting to be more competitive and to improve the performance. Management can also achieve financial information in real time through the application of ERP systems. This system will facilitate management to access the most up-to-date information such as planning, monitoring and evaluating the business processes of the organization to be more effective.
On the practical side, the Enterprise Resource Planning (ERP) system was applied to the General Company for Vegetable Oils to demonstrate a course in enhancing the accuracy of financial reporting.
... Show MoreIn 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.
Objective: A descriptive design, using the methodological approach, is carried throughout the present
study from April 1st 2012 to May 20th 2013 to construct the school physical environment standardized
features tool.
Methodology: An instrument of (141) item is constructed for the purpose of the study. A purposive
sample of (44) school; (22) public and (22) private ones is selected. Content Validity of the instrument is
determined through the use of panel of (11) expert who are specialists in Community Health Nursing and
Community Medicine. Internal consistency reliability, using the split-half technique, is employed through
the computation of Cronbach alpha correlation coefficient of (0.93) for internal scale. Data
Accurate emotion categorization is an important and challenging task in computer vision and image processing fields. Facial emotion recognition system implies three important stages: Prep-processing and face area allocation, feature extraction and classification. In this study a new system based on geometric features (distances and angles) set derived from the basic facial components such as eyes, eyebrows and mouth using analytical geometry calculations. For classification stage feed forward neural network classifier is used. For evaluation purpose the Standard database "JAFFE" have been used as test material; it holds face samples for seven basic emotions. The results of conducted tests indicate that the use of suggested distances, angles
... Show More1.Chapter I (systematic framework) which includes: the research problem and the importance of the research, the need for it, the goals of the research, the temporal &spatial boundaries, determine the terms and defined procedurally.2.Chapter II - the theoretical framework: It consists of three sections are:•The first topic:- the concept of references and experimentation in the theater. •The second topic:- the director of academic and experimentation in Iraq. Two paragraphs in this section came after the introduction, in first paragraph to talk about the Iraqi theater academic and experimentation, and in the second paragraph the researcher spoke about the academic director of the Iraqi and experimentation. 3.Chapter III - Actions -
... Show MoreMagnetic Resonance Imaging (MRI) uses magnetization and radio waves, rather than x-rays to make very detailed, cross- sectional pictures of the brain. In this work we are going to explain some procedures belongs contrast and brightness improvement which is very important in the improvement the image quality such as the manipulation with the image histogram. Its has been explained in this worked the histogram shrink i.e. reducing the size of the gray level gives a dim low contrast picture is produced, where, the histogram stretching of the gray level was distributed on a wide scale but there is no increase in the number of pixels in the bright region. The histogram equalization has also been discuss together with its effects of the improveme
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