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Membrane Computing for Real Medical Image Segmentation
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In this paper, membrane-based computing image segmentation, both region-based and edge-based, is proposed for medical images that involve two types of neighborhood relations between pixels. These neighborhood relations—namely, 4-adjacency and 8-adjacency of a membrane computing approach—construct a family of tissue-like P systems for segmenting actual 2D medical images in a constant number of steps; the two types of adjacency were compared using different hardware platforms. The process involves the generation of membrane-based segmentation rules for 2D medical images. The rules are written in the P-Lingua format and appended to the input image for visualization. The findings show that the neighborhood relations between pixels of 8-adjacency give better results compared with the 4-adjacency neighborhood relations, because the 8-adjacency considers the eight pixels around the center pixel, which reduces the required communication rules to obtain the final segmentation results. The experimental results proved that the proposed approach has superior results in terms of the number of computational steps and processing time. To the best of our knowledge, this is the first time an evaluation procedure is conducted to evaluate the efficiency of real image segmentations using membrane computing.

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Publication Date
Fri Jul 01 2022
Journal Name
Iop Conference Series: Earth And Environmental Science
Computer Model Application for Sorting and Grading Citrus Aurantium Using Image Processing and Artificial Neural Network
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Abstract<p>This study was conducted in College of Science \ Computer Science Department \ University of Baghdad to compare between automatic sorting and manual sorting, which is more efficient and accurate, as well as the use of artificial intelligence in automated sorting, which included artificial neural network, image processing, study of external characteristics, defects and impurities and physical characteristics; grading and sorting speed, and fruits weigh. the results shown value of impurities and defects. the highest value of the regression is 0.40 and the error-approximation algorithm has recorded the value 06-1 and weight fruits fruit recorded the highest value and was 138.20 g, Gradin</p> ... Show More
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Publication Date
Thu Dec 30 2021
Journal Name
Al-kindy College Medical Journal
Assessment of the Depression Level among Medical Students at University of Baghdad, College of Medicine
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Background: Depression, a state of low mood and aversion to activity, can affect people's thoughts, behavior, tendencies, feelings, and sense of well-being. It can either be short-term or long-term, depending on the severity of the person's condition. Risk factors include personal or family history of depression, major life changes, trauma, stress, certain physical illnesses, and medications.

Objective: This study investigates the prevalence of depression among medical students at the University of Baghdad, college of medicine in Iraq, and the association between some variables and depression.

Subjects and Methods: A cross-sectional study design with a convenience sampling method was conducted.

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Publication Date
Fri Apr 01 2016
Journal Name
Iosr Journal Of Computer Engineering
Lossless and Lossy Polynomial Image Compression
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Publication Date
Sun Jun 01 2014
Journal Name
Baghdad Science Journal
Image Steganography by Using Multiwavelet Transform
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Steganography is the art of secret communication. Its purpose is to hide the presence of information, using, for example, images as covers. The frequency domain is well suited for embedding in image, since hiding in this frequency domain coefficients is robust to many attacks. This paper proposed hiding a secret image of size equal to quarter of the cover one. Set Partitioning in Hierarchal Trees (SPIHT) codec is used to code the secret image to achieve security. The proposed method applies Discrete Multiwavelet Transform (DMWT) for cover image. The coded bit stream of the secret image is embedded in the high frequency subbands of the transformed cover one. A scaling factors ? and ? in frequency domain control the quality of the stego

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Publication Date
Fri Oct 01 2010
Journal Name
Iraqi Journal Of Physics
Smoothing Image using Adaptive Median Filter
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Median filter is adopted to match the noise statistics of the degradation seeking good quality smoothing images. Two methods are suggested in this paper(Pentagonal-Hexagonal mask and Scan Window Mask), the study involved modified median filter for improving noise suppression, the modification is considered toward more reliable results. Modification median filter (Pentagonal-Hexagonal mask) was found gave better results (qualitatively and quantitatively ) than classical median filters and another suggested method (Scan Window Mask), but this will be on the account of the time required. But sometimes when the noise is line type the cross 3x3 filter preferred to another one Pentagonal-Hexagonal with few variation. Scan Window Mask gave bett

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Publication Date
Fri Apr 01 2016
Journal Name
Iosr Journal Of Computer Engineering
Lossless and Lossy Polynomial Image Compression
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Publication Date
Sat Jul 01 2017
Journal Name
Diyala Journal For Pure Science
Correlated Hierarchical Autoregressive Models Image Compression
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Publication Date
Mon Jan 02 2012
Journal Name
Ibn Al-haitham Journal For Pure And Applied Science
Image encryption technique using Lagrange interpolation
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Publication Date
Wed Jan 30 2019
Journal Name
Journal Of The College Of Education For Women
Image Hiding Using Discrete Cosine Transform
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Steganography is a mean of hiding information within a more obvious form of
communication. It exploits the use of host data to hide a piece of information in such a way
that it is imperceptible to human observer. The major goals of effective Steganography are
High Embedding Capacity, Imperceptibility and Robustness. This paper introduces a scheme
for hiding secret images that could be as much as 25% of the host image data. The proposed
algorithm uses orthogonal discrete cosine transform for host image. A scaling factor (a) in
frequency domain controls the quality of the stego images. Experimented results of secret
image recovery after applying JPEG coding to the stego-images are included.

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Publication Date
Mon Jan 01 2007
Journal Name
2007 Ieee International Conference On Signal Processing And Communications
Fast Multi-level Image Vector Quantization
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