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Hybrid Methodology for Image Segmentation Based on Active Contour Module and Alpha-Shape Theory
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The concept of the active contour model has been extensively utilized in the segmentation and analysis of images. This technology has been effectively employed in identifying the contours in object recognition, computer graphics and vision, biomedical processing of images that is normal images or medical images such as Magnetic Resonance Images (MRI), X-rays, plus Ultrasound imaging. Three colleagues, Kass, Witkin and Terzopoulos developed this energy, lessening “Active Contour Models” (equally identified as Snake) back in 1987. Being curved in nature, snakes are characterized in an image field and are capable of being set in motion by external and internal forces within image data and the curve itself in that order. The present study proposes the use of a hybrid image segmentation technique to acquire precise segmentation outcomes, while engaging “Alpha Shape (α-Shape)” in supposition to derive the original contour, followed by a refining process through engaging a conventional active contour model. Empirical results show high potential in the suggested computational method. Trials indicate that the primary contour is capable of being precisely set next to the objective contour and effectively have these objective contours extracted, devoid of any contour instigation. Some of the benefits associated with the novel hybrid contour include minimized cost of computation, enhanced anti-jamming capability, as well as enlarged utilization array of snake model.

Publication Date
Sat Aug 01 2015
Journal Name
International Journal Of Computer Science And Mobile Computing
Image Compression based on Non-Linear Polynomial Prediction Model
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Publication Date
Wed May 06 2015
Journal Name
16th Conference In Natural Science And Mathematics
Efficient digital Image filtering method based on fuzzy algorithm
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Recently, Image enhancement techniques can be represented as one of the most significant topics in the field of digital image processing. The basic problem in the enhancement method is how to remove noise or improve digital image details. In the current research a method for digital image de-noising and its detail sharpening/highlighted was proposed. The proposed approach uses fuzzy logic technique to process each pixel inside entire image, and then take the decision if it is noisy or need more processing for highlighting. This issue is performed by examining the degree of association with neighboring elements based on fuzzy algorithm. The proposed de-noising approach was evaluated by some standard images after corrupting them with impulse

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Publication Date
Sat Jul 01 2023
Journal Name
International Journal Of Computing And Digital Systems
Human Identification Based on SIFT Features of Hand Image
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Publication Date
Mon May 11 2020
Journal Name
Baghdad Science Journal
Moving Objects Detection Based on Frequency Domain: image processing
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In this research a proposed technique is used to enhance the frame difference technique performance for extracting moving objects in video file. One of the most effective factors in performance dropping is noise existence, which may cause incorrect moving objects identification. Therefore it was necessary to find a way to diminish this noise effect. Traditional Average and Median spatial filters can be used to handle such situations. But here in this work the focus is on utilizing spectral domain through using Fourier and Wavelet transformations in order to decrease this noise effect. Experiments and statistical features (Entropy, Standard deviation) proved that these transformations can stand to overcome such problems in an elegant way.

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Publication Date
Mon Dec 16 2024
Journal Name
Light & Engineering
The Design and Experimental Realization of a Laser-Based Heating System Using Recycled Laser Module
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Laser is a powerful device that has a wide range of applications in fields ranging from materials science and manufacturing to medicine and fibre optic communications. One remarkable

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Publication Date
Mon Aug 01 2016
Journal Name
Journal Of Economics And Administrative Sciences
Knowledge value added methodology between theory and application Comparative filed research in some of the Iraqi private banks
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Abstract

        The research to have a clear perceptions about the knowledge value added to assess the knowledge resources of the Iraqi private banks, depending on the value added methodology of the proposed defined (Housel & Bell, 2001), which assumes that the  knowledge value added come through synergetic relationship between knowledge resource and information technology, trying to the possibility of mainstream theory and its application in the Iraqi environment and interpretation of results, and on this basis was launched search of a research problem took root synergetic nature of the relationship between knowledge (human)  resource and

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Publication Date
Tue Jun 01 2021
Journal Name
Baghdad Science Journal
A New Methodology to Find Private Key of RSA Based on Euler Totient Function
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          The aim of this paper is to present a new methodology to find the private key of RSA. A new initial value which is generated from a new equation is selected to speed up the process. In fact, after this value is found, brute force attack is chosen to discover the private key. In addition, for a proposed equation, the multiplier of Euler totient function to find both of the public key and the private key is assigned as 1. Then, it implies that an equation that estimates a new initial value is suitable for the small multiplier. The experimental results show that if all prime factors of the modulus are assigned larger than 3 and the multiplier is 1, the distance between an initial value and the private key

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Publication Date
Thu Jan 20 2022
Journal Name
Webology
Hybrid Intrusion Detection System based on DNA Encoding, Teiresias Algorithm and Clustering Method
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Until recently, researchers have utilized and applied various techniques for intrusion detection system (IDS), including DNA encoding and clustering that are widely used for this purpose. In addition to the other two major techniques for detection are anomaly and misuse detection, where anomaly detection is done based on user behavior, while misuse detection is done based on known attacks signatures. However, both techniques have some drawbacks, such as a high false alarm rate. Therefore, hybrid IDS takes advantage of combining the strength of both techniques to overcome their limitations. In this paper, a hybrid IDS is proposed based on the DNA encoding and clustering method. The proposed DNA encoding is done based on the UNSW-NB15

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Publication Date
Fri Apr 15 2016
Journal Name
International Journal Of Computer Applications
Hybrid Techniques based Speech Recognition
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Information processing has an important application which is speech recognition. In this paper, a two hybrid techniques have been presented. The first one is a 3-level hybrid of Stationary Wavelet Transform (S) and Discrete Wavelet Transform (W) and the second one is a 3-level hybrid of Discrete Wavelet Transform (W) and Multi-wavelet Transforms (M). To choose the best 3-level hybrid in each technique, a comparison according to five factors has been implemented and the best results are WWS, WWW, and MWM. Speech recognition is performed on WWS, WWW, and MWM using Euclidean distance (Ecl) and Dynamic Time Warping (DTW). The match performance is (98%) using DTW in MWM, while in the WWS and WWW are (74%) and (78%) respectively, but when using (

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Publication Date
Sun Feb 25 2024
Journal Name
Baghdad Science Journal
Hybrid CNN-based Recommendation System
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Recommendation 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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Scopus (7)
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