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Article
LEARNING TRADITIONAL FILTERS BASED ON IMAGE EXAMPLES

Author: Sarab M. Hameed
Journal: Al-Nahrain Journal of Science مجلة النهرين للعلوم ISSN: (print)26635453,(online)26635461 Year: 2007 Volume: 10 Issue: 1 Pages: 150-154
Publisher: Al-Nahrain University جامعة النهرين

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Abstract

This paper presents an approach for image filtering process depends on image examples. The approach involves of preparing a training images, in which a pair of images, with one image purported to be a filtered version of the other, as a training data. The filtered property is to be automatically learned and transferred to another target image. The basic idea behind learning approach is depended on luminance neighborhood statistics. Statistics pertaining to each pixel in the target pair are to be compared against statistics for every pixel in the source pair, and the closest match is to be found and its property (i.e., luminance information) is applied to the target image in order to create a filtered image. This approach is simple and provides results comparable to that obtained in image analogies of the Hertzmann et al.

يقدم هذا البحث طريقة لعملية ترشيح الصورة بالاعتماد على امثلة صور. تتضمن الطريقة تحضير صور التدريب، والتي هي زوج من الصور احدهما تمثل النسخة المرشحة للاخرى كبيانات تدريب. خاصية الترشيح ستتعلم بصورة اوتوماتكية وتتنقل هذه الخاصية الى صورة الهدف . إنّ الفكرةَ الأساسيةَ وراء طريقة التَعَلّم مُعتَمَدة على إحصائياتِ الجوارِ. الإحصائيات تَخْصُّ إلى كل نقطة شاشة في زوجِ الهدفَ سَتُقَارنُ ضدّ الإحصائياتِ لكل نقطة شاشة في الزوجِ المصدريِ، ونجد النظير الأقرب وخاصيته(معلومة الاضاءة) تطبق إلى صورةِ الهدفَ لكي تَكون صورةً مرشحة. هذه الطريقةِ بسيطةُ واعطت نتائج مشابه إلى تلك حَصلتْ عليها في تناظرات الصورةَ لـ Hertzmann واخرون.


Article
A GENETIC ALGORITHM FOR LEARNING IMAGE BLUR AND SHARPEN FILTERS

Author: Sarab M. Hameed
Journal: Al-Nahrain Journal of Science مجلة النهرين للعلوم ISSN: (print)26635453,(online)26635461 Year: 2007 Volume: 10 Issue: 2 Pages: 168-171
Publisher: Al-Nahrain University جامعة النهرين

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Abstract

In this paper, N-Queens problem was chosen to compare GA with PSO performance. GA with its own simple operators is stable in its performance under different search space sizes, while the PSO performs well in small search space size and its capabilities when space size becomes larger. This paper presents an approach for learning traditional image filters (blurring and sharpening). The concept of learning is based on the mechanism of Genetic algorithm (GA). By GA, filters applied on one source image can be learned and then used to process automatically another target image. By this way, blurring and sharpening can be implicitly deduced and applied without requiring to mathematically defining (i.e. explicitly) them. The proposed approach is simple and can provide good results; however, applying the filter directly is much more efficient.


Article
A Steganographic Approach Based on Spetial Frequency Layering

Author: Sarab M. Hameed
Journal: Al-Nahrain Journal of Science مجلة النهرين للعلوم ISSN: (print)26635453,(online)26635461 Year: 2006 Volume: 9 Issue: 2 Pages: 69-72
Publisher: Al-Nahrain University جامعة النهرين

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Article
Cryptanalytic Attack on Merkle- Hellman Knapsack Based on Diploid Genetic Algorithm

Author: Sarab M. Hameed
Journal: Al-Nahrain Journal of Science مجلة النهرين للعلوم ISSN: (print)26635453,(online)26635461 Year: 2006 Volume: 9 Issue: 2 Pages: 73-77
Publisher: Al-Nahrain University جامعة النهرين

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Article
PARTICLES SWARM OPTIMIZATION FOR THE CRYPTANALYSIS OF TRANSPOSITION CIPHER

Authors: Sarab M. Hameed --- Dalal N. Hmood
Journal: Al-Nahrain Journal of Science مجلة النهرين للعلوم ISSN: (print)26635453,(online)26635461 Year: 2010 Volume: 13 Issue: 4 Pages: 211-215
Publisher: Al-Nahrain University جامعة النهرين

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Abstract

Transposition ciphers are a class of historical encryption algorithms based on rearranging unitsof plaintext according to some fixed permutation which acts as the secret key. This paper presents anew investigation for cryptanalysis transposition cipher based on Particle Swarm Optimization(PSO). PSO is utilized for the automatic recovery of the key, and hence the plaintext, from only thecipher text. Based upon a mathematical model of the social interactions of swarms, the algorithmhas been shown to be effective at finding good solutions. Experimental results show the ability ofPSO in finding the correct secret key which is used to recover the plaintext.


Article
User Authentication via Mouse Dynamics

Authors: Osama A. Salman --- Sarab M. Hameed
Journal: Iraqi Journal of Science المجلة العراقية للعلوم ISSN: 00672904/23121637 Year: 2018 Volume: 59 Issue: 2B Pages: 963-968
Publisher: Baghdad University جامعة بغداد

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Abstract

Nowadays, the development of internet communication and the significant increase of using computer lead in turn to increasing unauthorized access. The behavioral biometric namely mouse dynamics is one means of achieving biometric authentication to safeguard against unauthorized access. In this paper, user authentication models via mouse dynamics to distinguish users into genuine and imposter are proposed. The performance of the proposed models is evaluated using a public dataset consists of 48 users as an evaluation data, where the Accuracy (Acc), False Reject Rate (FRR), and False Accept Rate (FAR) as an evaluation metrics. The results of the proposed models outperform related model considered in the literature


Article
A new Color image Encryption based on multi Chaotic Maps

Authors: Ibtisam A.Taqi --- Sarab M. Hameed
Journal: Iraqi Journal of Science المجلة العراقية للعلوم ISSN: 00672904/23121637 Year: 2018 Volume: 59 Issue: 4B Pages: 2117-2127
Publisher: Baghdad University جامعة بغداد

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Abstract

This paper presents a new RGB image encryption scheme using multi chaotic maps. Encrypting an image is performed via chaotic maps to confirm the properties of secure cipher namely confusion and diffusion are satisfied. Also, the key sequence for encrypting an image is generated using a combination of 1D logistic and Sine chaotic maps. Experimental results and the compassion results indicate that the suggested scheme provides high security against several types of attack, large secret keyspace and highly sensitive.


Article
IMAGE INPAINTING BASED ON PARTICLE SWARM PTIMIZATION
صبغ الصورة بالاعتماد على افضل سرب طيور

Authors: Mahmood A. Othman --- Nasreen J. Kadhim --- Sarab M. Hameed
Journal: Iraqi Journal of Science المجلة العراقية للعلوم ISSN: 00672904/23121637 Year: 2009 Volume: 50 Issue: 2 Pages: 231-235
Publisher: Baghdad University جامعة بغداد

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Abstract

Digital image inpainting is a technique that can repair a portion of damaged or removed image by means of automatic mechanisms.
This paper proposes an automatic approach for reconstruction of small missing or damaged portions of images using Particle Swarm Optimization (PSO). The PSO inpainting approach attempts to find the best match between Red, Green, and Blue (RGB) channels of the pixels masked (i.e. pixels of the region to be removed) and pixels in the surrounding area, and transfer the color of the best matching. The results show that our mechanism is more efficient (i.e. less time required to inpaint the masked region) when compared with genetic - based image inpainting.
Keywords:Image Inpainting, Image Restoration, Particle Swarm Optimization

صبغ الصور الرقمية هي تقنية لتصليح الجزء المخرب او حذف من الصورة بطريقة آلية. يقترح هذا البحث طريقة لإعادة الجزء المخرب باستخدام أفضل سرب طيور. يحاول PSO الصبغ عن طريق إيجاد أفضل تطابق بين القنوات الأحمر والأخضر والأزرق للنقطة المغطاة ( النقطة المراد حذفها) والنقاط المحاطة بهذه النقطة ثم نقل اللون لافضل تطابق. أثبتت النتائج بان الطريقة المقترحة اكفاْ(تحتاج وقت قليل) عند مقارنتها مع صبغ الصورة المعتمد على الخوارزمية الجينية.

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Article
Image Steganography in De-Correlated Color Spaces

Authors: Dr. Sarab M. Hameed --- Sura N. Abdula --- Fatin A. Dawood
Journal: Al-Nahrain Journal of Science مجلة النهرين للعلوم ISSN: (print)26635453,(online)26635461 Year: 2006 Volume: 9 Issue: 1 Pages: 34-40
Publisher: Al-Nahrain University جامعة النهرين

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Article
Genetic Algorithm based Clustering for Intrusion Detection
العنقدة على أساس الخوارزميات الجينية لكشف التسلل

Authors: Noor Fouad نور فؤاد --- Sarab M. Hameed سراب مجيد حميد
Journal: Iraqi Journal of Science المجلة العراقية للعلوم ISSN: 00672904/23121637 Year: 2017 Volume: 58 Issue: 2B Pages: 929-938
Publisher: Baghdad University جامعة بغداد

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Abstract

Clustering algorithms have recently gained attention in the related literature since they can help current intrusion detection systems in several aspects. This paper proposes genetic algorithm (GA) based clustering, serving to distinguish patterns incoming from network traffic packets into normal and attack. Two GA based clustering models for solving intrusion detection problem are introduced. The first model coined as GA #1 handles numeric features of the network packet, whereas the second one coined as GA #2 concerns all features of the network packet. Moreover, a new mutation operator directed for binary and symbolic features is proposed. The basic concept of proposed mutation operator depends on the most frequent value of the features using mode operator. The proposed GA-based clustering models are evaluated using Network Security Laboratory-Knowledge Discovery and Data mining (NSL-KDD) benchmark dataset. Also, it is compared with two baseline methods namely k-means and k-prototype to judge their performance and to confirm the value of the obtained clustering structures. The experiments demonstrate the effectiveness of the proposed models for intrusion detection problem in which GA #1 and GA #2 models outperform the two baseline methods in accuracy (Acc), detection rate (DR) and true negative rate (TNR). Moreover, the results prove the positive impact of the proposed mutation operator to enhance the strength of GA#2 model in all evaluation metrics. It successfully attains 6.4, 5.463 and 3.279 percentage of relative improvement in Acc over GA #1 and baseline models respectively.

مؤخراً حصلت خوارزميات التجميع على اهتمام من قبل البحوث ذات العلاقة حيث تساعد أنظمة الكشف الحالية في نواحي عدة . هذا البحث يقترح الخوارزمية الجنية باعتماد على تقنية التجميع , حيث تساعد لتمييز الأنماط القادمة الى الشبكة فيما اذا كانت نمط طبيعي او نمط هجومي. تم تقديم نموذجين لمشكلة كشف التسلل النموذج الأول أطلق عليه أسم GA #1 حيث يتعامل مع ميزات حزمة شبكة الرقمية ، بينما اطلق على النموذج الثاني GA #2 التي تتعامل مع كل ميزات حزمة الشبكة. علاوة على ذلك , تم اقتراح معامل طفرة جديد لميزات الثنائية والرمزية لحزمة الشبكة . حيث ان المفهوم الرئيسي للمعامل الطفرة المقترح يعتمد على القيمة الاكثر تكرار للميزات حزمة الشبكة باستخدام معامل . mode ولغرض تقييم الخوارزمية الجينية باعتماد على تقنية التجميع المقترحة لكشف التسلل يتم باستخدام مجموعة بيانات NSL-KDD ومقارنتها مع طريقتين هما k-means, k-prototype للحكم على أدائها وأثبات القيم التي تم الحصول عليها من التجميع .اتثبت التجارب العملية فعالية النماذج المقترحة لمشكلة كشف التسلل . أن نماذج المقترحة GA # 1 و GA # 2 تمتاز بأداء متفوق على الأساليب التقليدية في كافة المقاييس من حيث مقياس( ACC)، كشف معدل الكشف (DR) ومعدل سلبي صحيح (TNR). وعلاوة على ذلك، فإن النتائج ثبتت الأثر الإيجابي للعامل الطفرة المقترح لمضاعفة قوة نموذج الثاني GA #2 في كل المقاييس التقييم. حيث حصلت GA #2 على اعلى تحسن نسبي مئوي في معيار الدقة 6.4، 5.463 و 3.279 بالنسبة الى GA #1 و الطرق التقليدية.

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