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Painterly Rendering by Using K-mean Segmentation
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    The problem statement discussed in this paper is a new technique for the presentation of painterly rendering that uses a K-mean segmentation to divide the input image into a set of regions (depending on the grayscale of the regions). Segmenting the input image helps users use different brush strokes and easily change the strokes' shape, size, or orientation for different regions. Every region is painted using different brush kinds. The properties of the brush strokes are chosen depending on the region's details. The brush stroke properties, such as size, color, shape, location, and orientation, are extracted from the source image using statistical tools. The number of regions is set up manually and depends on the input image. This method allows the user to apply different painting styles to different regions and create a painterly rendering. MATLAB is used to render the images into paintings.

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Publication Date
Mon Jan 27 2020
Journal Name
Iraqi Journal Of Science
Quantum Image Watermarking Based on Wavelet and Geometric Transformation
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Like the digital watermark, which has been highlighted in previous studies, the quantum watermark aims to protect the copyright of any image and to validate its ownership using visible or invisible logos embedded in the cover image. In this paper, we propose a method to include an image logo in a cover image based on quantum fields, where a certain amount of texture is encapsulated to encode the logo image before it is included in the cover image. The method also involves transforming wavelets such as Haar base transformation and geometric transformation. These combination methods achieve a high degree of security and robustness for watermarking technology. The digital results obtained from the experiment show that the values of Peak Sig

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Publication Date
Thu Dec 19 2024
Journal Name
Journal Of The College Of Basic Education
Fuzzy Nonparametric Regression Model Estimation Based on some Smoothing Techniques With Practical Application
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In this research, we use fuzzy nonparametric methods based on some smoothing techniques, were applied to real data on the Iraqi stock market especially the data about Baghdad company for soft drinks for the year (2016) for the period (1/1/2016-31/12/2016) .A sample of (148) observations was obtained in order to construct a model of the relationship between the stock prices (Low, high, modal) and the traded value by comparing the results of the criterion (G.O.F.) for three techniques , we note that the lowest value for this criterion was for the K-Nearest Neighbor at Gaussian function .

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Publication Date
Sat Jan 20 2024
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Cubic Of Positive Implicative Ideals In KU- Semigroup
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In this paper, we define a cubic positive implicative-ideal, a cubic implicative-ideal and a cubic commutative-ideal of a semigroup in KU-algebra as a generalization of a fuzzy (positive implicative-ideal, an implicative-ideal and a commutative-ideal) of a semigroup in KU-algebra. Some relations between these types of cubic ideals are discussed. Also, some important properties of these ideals are studied. Finally, some important theories are discussed. It is proved that every cubic commutative-ideal, cubic positive implicative-ideal, and cubic implicative-ideal are a cubic ideal, but not conversely. Also, we show that if Θ is a cubic positive implicative-ideal and a cubic commutative-ideal then Θ is a cubic implicative-ideal. Some exam

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Publication Date
Wed Dec 01 2021
Journal Name
Journal Of Economics And Administrative Sciences
Comparison of Some Non-Parametric Quality Control Methods
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    Multivariate Non-Parametric control charts were used to monitoring the data that generated by using the simulation, whether they are within control limits or not. Since that non-parametric methods do not require any assumptions about the distribution of the data.  This research aims to apply the multivariate non-parametric quality control methods, which are Multivariate Wilcoxon Signed-Rank ( ) , kernel principal component analysis (KPCA) and k-nearest neighbor (

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Publication Date
Mon Mar 01 2021
Journal Name
Iraqi Journal Of Physics
Enhancement CT Scan Image and Study Electronic, Structural and Vibrational Properties of Iobenguane
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This work is divided into two parts first part study electronic structure and vibration properties of the Iobenguane material that is used in CT scan imaging. Iobenguane, or MIBG, is an aralkylguanidine analog of the adrenergic neurotransmitter norepinephrine and a radiopharmaceutical. It acts as a blocking agent for adrenergic neurons. When radiolabeled, it can be used in nuclear medicinal diagnostic techniques as well as in neuroendocrine antineoplastic treatments. The aim of this work is to provide general information about Iobenguane that can be used to obtain results to diagnose the diseases. The second part study image processing techniques, the CT scan image is transformed to frequency domain using the LWT. Two methods of contrast

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Publication Date
Thu Mar 02 2023
Journal Name
East European Journal Of Physics
Evaluation of the Influence of Body Mass Index and Signal-to-Noise Ratio on the PET/CT Image Quality in Iraqi Patients with Liver Cancer
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Image quality has been estimated and predicted using the signal to noise ratio (SNR). The purpose of this study is to investigate the relationships between body mass index (BMI) and SNR measurements in PET imaging using patient studies with liver cancer. Three groups of 59 patients (24 males and 35 females) were divided according to BMI. After intravenous injection of 0.1 mCi of 18F-FDG per kilogram of body weight, PET emission scans were acquired for (1, 1.5, and 3) min/bed position according to the weight of patient. Because liver is an organ of homogenous metabolism, five region of interest (ROI) were made at the same location, five successive slices of the PET/CT scans to determine the mean uptake (signal) values and its standard deviat

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Publication Date
Sat Apr 15 2023
Journal Name
Journal Of Robotics
A New Proposed Hybrid Learning Approach with Features for Extraction of Image Classification
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Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class

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Publication Date
Thu Apr 27 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
New Adaptive Satellite Image Classification Technique for Al habbinya Region West of Iraq
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   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

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Publication Date
Sat Dec 31 2011
Journal Name
Al-khwarizmi Engineering Journal
Path Planning Control for Mobile Robot
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Autonomous motion planning is important area of robotics research. This type of planning relieves human operator from tedious job of motion planning. This reduces the possibility of human error and increase efficiency of whole process.

This research presents a new algorithm to plan path for autonomous mobile robot based on image processing techniques by using wireless camera that provides the desired image for the unknown environment . The proposed algorithm is applied on this image to obtain a optimal path for the robot. It is based on the observation and analysis of the obstacles that lying in the straight path between the start and the goal point by detecting these obstacles, analyzing and studying their shapes, positions and

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Publication Date
Tue Jun 01 2021
Journal Name
Journal Of The College Of Languages (jcl)
Socialist Realism And The Situation Of Women In Society In The Works Of Maxim Gorky "Mother": Социалистический Реализм И Положение Женщины В Обществе В Произведении Максима Горького "Мать"
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            Maxim Gorky’s Mother is one of the most important literary genre in social realism, in which he depicts female characters with revolutionary fervor and enthusiasm, projecting his social ideologies and dreams. Though the novel unique importance lies in the fact that it has been thoroughly analyzed by many writers, historians and sociologists, there are almost no studies devoted to the role of women out of a Marxist and feminist point of view. The present paper sheds light on the Russian woman‘s important role in overcoming all adversity and gain her position on Social Realism.

Одно из центральных мест сре

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