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Article
Compare between A.H. SH Quintet mask and Ant Colony for Mycosis Fungoides Skin image Edge detection

Authors: Ali Hassan Nasser Al-Fayadh --- Hind Rostom Mohamed --- Shayma Maki kadham
Journal: journal of kerbala university مجلة جامعة كربلاء ISSN: 18130410 Year: 2012 Volume: 10 Issue: 3 Pages: 96-104
Publisher: Kerbala University جامعة كربلاء

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Abstract

In this paper, in first stage Ant Colony Optimization (ACO) is introduced to tackle the image edge detection problem, where the aim is to extract the edge information presented in the image, since it is crucial to understand the image’s content. The second stage .A.H. SH Quintet mask Appling for same images to find edge detection. The proposed approach exploits a number of ants, which move on the image driven by the local variation of the image’s intensity values, to establish a pheromone matrix, which represents the edge information at each pixel location for Mycosis Fungoides Skin image Edge detection is proposed.The third stage compare between first and second stage for Mycosis Fungoides disease. The Skin image have been identified and the edges of the images used for each and every stages that the database consists of 40 images divided each stage of the Mycosis Fungoides disease Skin image 10 images. For each stage a novel algorithm which combines pixel and region based color segmentation techniques is used. The experimental results confirm the effectiveness of the proposed algorithms

المرحلة الأولى في هذه الورقة تتكلم عن مستعمرة النمل المثالية (ACO) لكشفِ حافةِ صورةِ مرض جلدِ Mycosis Fungoides المُقتَرَحُ حيث إن الهدف من انتزاع محتوى الصورة هو فهم محتوى الصورة إما المرحلة الثانية تتكلم عن الماسك الجديد تحت عنوان (.A.H. SH Quintet mask) لنفس الصور وإما المرحلة الثالثة هي المقارنة بين المرحلة الأولى والثانية للحافات المنتزعة لنفس الصور حيث أنها . قدّمتْ إلى الأربعة مِنْ مراحلِ صورةِ مرضِ جلدِ Mycosis Fungoides مُيّزتْ وحافاتَ الصورِ استعملت لكُلّ مراحل التي قاعدة البيانات تَشْملُ 40 صورةِ قسّمتْ كُلّ مرحلة صورةِ جلدِ مرضِ صورِ Mycosis Fungoides الـ10. لكُلّ مرحلة لخوارزمية مبتكرة التي تَدْمجُ نقطةَ الشاشة والمنطقةَ أسندتَا تقنياتَ انقسام لونِ مستعملةُ. تُؤكّدُ النَتائِجُ التجريبيةُ فعالية المُقتَرَحينِ


Article
Comparison Between Classical Masks and (Odd and Even) Groups Masks for Mycosis Fungoides Disease Skin Image Edges Detection

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Abstract

In the present paper, a comparisonbetween classical masks and (odd and even)masks groups for Mycosis Fungoides diseaseSkin image edges detection is performed.The goal is to extract the information known inthe image because it is vital to understand theimage content as the proposed approach is thecomparative edge by masks classical and a newset of Groups masks (odd and even ) whichconsist of 10 masks. The database consists of40 images reprints different stage of theMycosis Fungoides disease Skin images 10images for each stage. The experimental resultsconfirm the effectiveness of the proposedsystem. and confirm the effectiveness of theproposed(odd and even) Groups masks.


Article
H.SH.Rostom Utilization of improved masks for edge detection images

Authors: Dr. Ali H. Naser --- Hind Rostom --- Shaymaa Maki
Journal: Iraqi Journal of Information Technology المجلة العراقية لتكنولوجيا المعلومات ISSN: 19948638/26640600 Year: 2014 Volume: 6 Issue: 1 اللغة الانكليزية Pages: 57-68
Publisher: iraqi association of information الجمعية العراقية لتكنولوجيا المعلومات

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Abstract

In the present paper, algorithm is proposed to create a connected boundaries components using the local features minutiae points in image as objects image called (A. H.SH.Rostom) algorithm The Group of (A. H.SH.Rostom) algorithm consists of 10 masks were geometry of the mask operator determines a characteristic direction in which it is most sensitive to edges applied to the four stages of the Mycosis Fungoides disease Skin image have been identified and the edges of the images used for each and every stages that the database consists of 40 images divided each stage of the Mycosis Fungoides disease Skin image 10 images. The experimental results confirm the effectiveness of the proposed A. H.SH.Rostom Utilization of improved masks for Image Edge Detecting of Mycosis Fungoides.

تم اقتراح خوارزمية لإنشاء مكونات حدود المكونات باستخدام خصائص مميزة للتفاصيل المحلية في الصورة سميت الخوارزمية باسم A.H.SH.Rostom تتكون الخوارزمية من عشرة اقنعة تحدد الالية المستخدمة لتحديد الاتجاه بحيث يكون الاكثر دقة. استخدمت لتحديد حواف مرض Mycosis Fungoides علما ان قاعدة البيانات تتكون من 40 صورة عشرة صور في كل مرحله . اثبتت النتائج التجريبية فعالية الخوارزمية وامكانية تحديد حواف مرض Mycosis Fungoides

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