تحليل النماذج في الصور والتعرف عليها باستخدام الشبكات العصبونية

Authors

  • سهى عراج

Abstract

يقدم البحث طريقة مطورة لكشف مكان نموذج الوجه في الصورة, وذلك بجمع أكثر من تقنية لتحقيق أفضل نسبة كشف. يبنى نموذج لون بشرة باستخدام الفضاء اللوني (RGB) Red, Green, Blue, لكشف مناطق البشرة وينتج المناطق المرشحة لتكون الوجه في الصورة. ومن خلال تقنية الشبكة العصبونية يتم تدريب مجموعة من صور الوجوه وصور لغير الوجوه (الخلفية) ، بعد إسقاطها على حيز جزئي بواسطة تقنية تحليل المعاملات الأولية بهدف تقليل أبعاد صور التدريب وتقليل الزمن الحسابي. يوجد تعديلين للاستخدام التقليدي للشبكة العصبونية وهما: أولاً, تختبر الشبكة العصبونية مناطق الصورة المرشحة لتكون وجوه فقط, بالنتيجة يتم تقليل حيز البحث. ثانياً, يتم تكييف نافذة مسح الشبكة العصبونية لصورة الدخل, بحيث تعتمد على حجم المنطقة المرشحة لتكون وجه مما يمكن نظام الكشف من كشف الوجوه بحجوم متعددة.

A new face detection system is presented. The system combines several techniques for face detection to achieve better detection rates, a skin colormodel based on RGB color space is built and used to detect skin regions. The detected skin regions are the face candidate regions. Neural network is used and trained with training set of faces and non-faces that projected into subspace by principal component analysis technique. we have added two modifications for the classical use of neural networks in face detection. First, the neural network tests only the face candidate regions for faces, so the search space is reduced. Second, the window size used by the neural network in scanning the input image is adaptive and depends on the size of the face candidate region. This enables the face detection system to detect faces with any size.

 

 

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Published

2016-07-07

How to Cite

1.
عراج س. تحليل النماذج في الصور والتعرف عليها باستخدام الشبكات العصبونية. Tuj-eng [Internet]. 2016Jul.7 [cited 2025Jul.11];37(1). Available from: https://www.journal.tishreen.edu.sy/index.php/engscnc/article/view/1577

Issue

Vol. 37 No. 1 (2015): العلوم الهندسية

Section

Articles

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Copyright (c) 2016 �ttps://creativecommons.org/licenses/by-nc-sa/4.0/

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