Image fusion is one of the most important techniques in digital image processing, includes the development of software to make the integration of multiple sets of data for the same location; It is one of the new fields adopted in solve the problems of the digital image, and produce high-quality images contains on more information for the purposes of interpretation, classification, segmentation and compression, etc. In this research, there is a solution of problems faced by different digital images such as multi focus images through a simulation process using the camera to the work of the fuse of various digital images based on previously adopted fusion techniques such as arithmetic techniques (BT, CNT and MLT), statistical techniques (LMM, RVS and WT) and spatial techniques (HPFA, HFA and HFM). As these techniques have been developed and build programs using the language MATLAB (b 2010). In this work homogeneity criteria have been suggested for evaluation fused digital image's quality, especially fine details. This criterion is correlation criteria to guess homogeneity in different regions within the image by taking a number of blocks of different regions in the image and different sizes and work shifted blocks per pixel. As dependence was on traditional statistical criteria such as (mean, standard deviation, and signal to noise ratio, mutual information and spatial frequency) and compared with the suggested criteria to the work. The results showed that the evaluation process was effective and well because it took into measure the quality of the homogenous regions.
the study considers the optical classification of cervical nodal lymph cells and is based on research into the development of a Computer Aid Diagnosis (CAD) to detect the malignancy cases of diseases. We consider 2 sets of features one of them is the statistical features; included Mode, Median, Mean, Standard Deviation and Maximum Probability Density and the second set are the features that consist of Euclidian geometrical features like the Object Perimeter, Area and Infill Coefficient. The segmentation method is based on following up the cell and its background regions as ranges in the minimum-maximum of pixel values. The decision making approach is based on applying of Minimum Dista
In the present work, pattern recognition is carried out by the contrast and relative variance of clouds. The K-mean clustering process is then applied to classify the cloud type; also, texture analysis being adopted to extract the textural features and using them in cloud classification process. The test image used in the classification process is the Meteosat-7 image for the D3 region.The K-mean method is adopted as an unsupervised classification. This method depends on the initial chosen seeds of cluster. Since, the initial seeds are chosen randomly, the user supply a set of means, or cluster centers in the n-dimensional space.The K-mean cluster has been applied on two bands (IR2 band) and (water vapour band).The textural analysis is used
... 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
... Show MoreDiabetic retinopathy is an eye disease in diabetic patients due to damage to the small blood vessels in the retina due to high and low blood sugar levels. Accurate detection and classification of Diabetic Retinopathy is an important task in computer-aided diagnosis, especially when planning for diabetic retinopathy surgery. Therefore, this study aims to design an automated model based on deep learning, which helps ophthalmologists detect and classify diabetic retinopathy severity through fundus images. In this work, a deep convolutional neural network (CNN) with transfer learning and fine tunes has been proposed by using pre-trained networks known as Residual Network-50 (ResNet-50). The overall framework of the proposed
... Show MoreThe aim of the study is to detect the malignant conditions of the skin tumors through the features of optical images. This research included some of image processing techniques to detect skin cancer as a strong threat to human beings' lives. Using image processing and analysis methods to improves the ability of pathologists to detect this disease leading to more specified diagnosis and better treatment of them. One hundred images were collected from Benign and Malignant tumors and some appropriate image features were calculated, like Maximum Probability, Entropy, Coefficient of Variation, Homogeneity and Contrast, and using Minimum Distance method to separate these images. These features with Minimum Distance as a proposed making decision a
... Show MoreA mathematical model has been introduced to investigate the effect of nuclear reaction constant ( A ), probability of the BEC ground state occupation Ω i, nD is the number density of deuteron (d) and the overall number of nuclei ND on the total nuclear d-d fusion rate (R). Under steady-state of the condensates of Bose-Einstein, the postulate of quantum theory and Bose-Einstein theory were applied to evaluate the total nuclear (d-d) fusion rate trapping in Nickel-metal The total nuclear fusion rate trapping predicts a strong relationship between astrophysical S-factor and masses of Nickel. The reaction rate trapping model was tested on three reaction d(d,p)T, d(d, n)3He and d(d, 4He)Q = 23.8MeV respectively. The reaction rate has described
... Show MoreBackground: Obesity tends to appear in modern societies and constitutes a significant public health problem with an increased risk of cardiovascular diseases.
Objective: This study aims to determine the agreement between actual and perceived body image in the general population.
Methods: A descriptive cross-sectional study design was conducted with a sample size of 300. The data were collected from eight major populated areas of Northern district of Karachi Sindh with a period of six months (10th January 2020 to 21st June 2020). The Figure rating questionnaire scale (FRS) was applied to collect the demographic data and perception about body weight. Body mass index (BMI) used for ass
... Show MoreWith its rapid spread, the coronavirus infection shocked the world and had a huge effect on billions of peoples' lives. The problem is to find a safe method to diagnose the infections with fewer casualties. It has been shown that X-Ray images are an important method for the identification, quantification, and monitoring of diseases. Deep learning algorithms can be utilized to help analyze potentially huge numbers of X-Ray examinations. This research conducted a retrospective multi-test analysis system to detect suspicious COVID-19 performance, and use of chest X-Ray features to assess the progress of the illness in each patient, resulting in a "corona score." where the results were satisfactory compared to the benchmarked techniques. T
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