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Automatic Facial Expression Classification Using Image Processing Technique ( Fear – disgust – sadness – Surprise – Anger – Happiness – Natural )

التصنيف الآلي لتعبيرات الوجه باستخدام تقنيات معالجة الصورة - الخوف الاشمئزاز الحزن التفاجؤ الغضب السعادة التعبير الطبيعي

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 Publication date 2013
and research's language is العربية
 Created by Shamra Editor




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This paper presents an algorithm for designing a system that classifies standard human facial expressions which are fear , disgust , sad , surprise , Anger , happiness , natural expression . The facial expression that is presented in the input image of the system can be classified depending on extracting appearance features , then they entered into neural network to complete the classification process using Matlab as a programming language.


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Research summary
تقدم هذه الرسالة نظامًا لتصنيف تعبيرات الوجه البشرية القياسية (الخوف، الاشمئزاز، الحزن، المفاجأة، الغضب، السعادة، التعبير الطبيعي) باستخدام تقنيات معالجة الصور. يتم تصنيف تعبير الوجه في الصورة المدخلة للنظام بناءً على استخراج سمات المظهر وإدخالها إلى شبكة عصبية (SOM) باستخدام لغة البرمجة Matlab. يتكون العمل من عدة مراحل تشمل تجميع الصور، المعالجة المسبقة، استخراج السمات، تدريب الشبكة العصبية، واختبار النظام. أظهرت النتائج أن النظام حقق أعلى نسبة تصنيف عند تعبير الغضب بنسبة 100%، بينما كانت أدنى نسبة عند تعبير الحزن بنسبة 50%. تعود نسبة الخطأ إلى إمكانية تصنيف الشبكة للشعور الموجود في الصورة إلى شعور آخر قريب منه بسبب المسافة الإقليدية. تم مقارنة النتائج مع دراسة مرجعية وأظهرت تحسنًا في بعض التعبيرات مثل الغضب، بينما كانت أقل دقة في تعبيرات أخرى مثل الحزن.
Critical review
دراسة نقدية: تعتبر هذه الرسالة خطوة مهمة في مجال التعرف على تعبيرات الوجه باستخدام الشبكات العصبية وتقنيات معالجة الصور. ومع ذلك، هناك بعض النقاط التي يمكن تحسينها. أولاً، يمكن زيادة حجم قاعدة البيانات المستخدمة في التدريب لتحسين دقة التصنيف. ثانيًا، يمكن تجربة أنواع أخرى من الشبكات العصبية للتحقق من تأثيرها على دقة التصنيف. ثالثًا، يمكن تحسين معالجة الصور المسبقة لتقليل الضجيج بشكل أكثر فعالية. وأخيرًا، يمكن دمج تقنيات أخرى مثل التعلم العميق لتحسين الأداء العام للنظام.
Questions related to the research
  1. ما هي التعبيرات الوجهية التي تم تصنيفها في هذه الدراسة؟

    التعبيرات الوجهية التي تم تصنيفها هي الخوف، الاشمئزاز، الحزن، المفاجأة، الغضب، السعادة، والتعبير الطبيعي.

  2. ما هي أعلى نسبة تصنيف حققها النظام؟

    أعلى نسبة تصنيف حققها النظام كانت عند تعبير الغضب بنسبة 100%.

  3. ما هي التقنية المستخدمة لاستخراج السمات من الصور؟

    التقنية المستخدمة لاستخراج السمات من الصور هي المرشح الغوصي (Gaussian filter).

  4. ما هي أسباب نسبة الخطأ في تصنيف التعبيرات؟

    تعود نسبة الخطأ إلى إمكانية تصنيف الشبكة للشعور الموجود في الصورة إلى شعور آخر قريب منه بسبب المسافة الإقليدية.


References used
N. Sebe, M. Lew, Y. Sun, I. Cohen, T. Gevers, and T. Huang, \Authentic facial expression analysis," Image and Vision Computing, vol. 25, no. 12, pp. 1856 .3113 ,0362
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