Fractal geometry is receiving increase attention as a quantitative and qualitative model for natural phenomena description, which can establish an active classification technique when applied on satellite images. In this paper, a satellite image is used which was taken by Quick Bird that contains different visible classes. After pre-processing, this image passes through two stages: segmentation and classification. The segmentation carried out by hybrid two methods used to produce effective results; the two methods are Quadtree method that operated inside Horizontal-Vertical method. The hybrid method is segmented the image into two rectangular blocks, either horizontally or vertically depending on spectral uniformity criterion; otherwise the block is segmented by the quadtree. Then, supervised classification is carried out by means the Fractal Dimension. For each block in the image, the Fractal Dimension was determined and used to classify the target part of image. The supervised classification process delivered five deferent classes were clearly appeared in the target part of image. The supervised classification produced about 97% classification score, which ensures that the adopted fractal feature was able to recognize different classes found in the image with high accuracy level.
In this paper, integrated quantum neural network (QNN), which is a class of feedforward
neural networks (FFNN’s), is performed through emerging quantum computing (QC) with artificial neural network(ANN) classifier. It is used in data classification technique, and here iris flower data is used as a classification signals. For this purpose independent component analysis (ICA) is used as a feature extraction technique after normalization of these signals, the architecture of (QNN’s) has inherently built in fuzzy, hidden units of these networks (QNN’s) to develop quantized representations of sample information provided by the training data set in various graded levels of certainty. Experimental results presented here show that
... Show MoreWe propose a new method for detecting the abnormality in cerebral tissues present within Magnetic Resonance Images (MRI). Present classifier is comprised of cerebral tissue extraction, image division into angular and distance span vectors, acquirement of four features for each portion and classification to ascertain the abnormality location. The threshold value and region of interest are discerned using operator input and Otsu algorithm. Novel brain slices image division is introduced via angular and distance span vectors of sizes 24˚ with 15 pixels. Rotation invariance of the angular span vector is determined. An automatic image categorization into normal and abnormal brain tissues is performed using Support Vector Machine (SVM). St
... Show MoreImage compression is very important in reducing the costs of data storage transmission in relatively slow channels. Wavelet transform has received significant attention because their multiresolution decomposition that allows efficient image analysis. This paper attempts to give an understanding of the wavelet transform using two more popular examples for wavelet transform, Haar and Daubechies techniques, and make compression between their effects on the image compression.
Publications are generally considered an effective visual artistic means that addresses the recipient (the audience), with the functional, aesthetic and expressive dimensions they carry that contribute to spreading a diverse cultural awareness, especially those publications that are concerned with their media, promotional and organizational performance, as well as specific cultural events at specific times, in pursuit Access to renewable and elaborate designs to achieve the functional and aesthetic purpose, as the completed design and construction process is subject to many variations, whether this diversity is intellectual or technical, internal or external, and all of them may overlap to obtain a comprehensive system of artistic format
... Show MoreThis study compared and classified of land use and land cover changes by using Remote Sensing (RS) and Geographic Information Systems (GIS) on two cities (Al-Saydiya city and Al-Hurriya) in Baghdad province, capital of Iraq. In this study, Landsat satellite image for 2020 were used for (Land Use/Land Cover) classification. The change in the size of the surface area of each class in the Al-Saydiya city and Al-Hurriya cities was also calculated to estimate their effect on environment. The major change identified, in the study, was in agricultural area in Al-Saydiya city compare with Al-Hurriya city in Baghdad province. The results of the research showed that the percentage of the green
Jean-Paul Sartre and Badr Shakir al-Sayyabe are among the most prominent writers that critiqued the destructive role of capitalism and the patriarchal power system in the period of the Post-World War II crisis. Divided into three chapters, the present study examines two of the most eminent literary works in the history of the Western and Eastern societies in the fifties of the last decade: Jean Paul Sartre’s play : The Respectful Prostitute and Badr Shaker al-Sayyabe’s poem: The Blind Prostitute.
Chapter one discusses the position of the prostitute in a patriarchal societies. Chapter two linguistically analy
... Show MoreThe current study was conducted on goats in various parts of Wasit Province, Iraq, from November 2021 to April 2022. The study aims to find and identify intestinal parasites (IPs) in goats in Wasit province. The goat's fresh fecal specimens (n=180) include cysts, eggs, oocysts, trophozoites and larval stages. One hundred eighty sheep feces samples were collected, and more than one parasite was isolated from one sample (mixed infection). According to the data acquired, the overall prevalence of intestinal parasites in goats was 52.77 (95 samples). In the current investigation, eleven distinct (IPs) species with infection rates were identified, including Toxocara vitulorum (Goeze, 1782) (16.66 %), Cryptosporidium sp.( Tyzzer, 1907) (1
... Show MoreThis research deals with the use of a number of statistical methods, such as the kernel method, watershed, histogram, and cubic spline, to improve the contrast of digital images. The results obtained according to the RSME and NCC standards have proven that the spline method is the most accurate in the results compared to other statistical methods.