A new method using naive bayes and RGBD facial identification based on extracted features from image pixels
المؤلف
المصدر
Engineering and Technology Journal
العدد
المجلد 39، العدد 4A (30 إبريل/نيسان 2021)، ص ص. 632-641، 10ص.
الناشر
تاريخ النشر
2021-04-30
دولة النشر
العراق
عدد الصفحات
10
التخصصات الرئيسية
الموضوعات
الملخص EN
Nowadays, life seems to have been resilient, particularly for those with physical disabilities.
Recognition of AV letters is one of the critical and famously the difficult structures.
This research has been developed based on the potential of the features in some applications than the statistical properties.
While, these features have been resolved the lip movement for AV letters recognition, Naive Bayesian and Red green blue and depth RGBD have been adopted for visual letter identification.
Naive Bayesian has 73.33% for usual recognition with three letters, each with ten frames, while RGBD classifier is 100% .
Within that for this case, two scenarios were made with different forms of noise placed on the face of normal, normal + 10% , normal + 25% and normal + 75% noise.
The first one trains and understands all classes, one after another.
While the other is training 95 percent of RGBD and 83.3 percent for Naive Bayesian with recognition of one of the inflicted forms.
RGBD identification is 100 percent for the second one, while 49.99 for the Naive Nowadays, life seems to have been resilient, particularly for those with physical disabilities.
Recognition of AV letters is one of the critical and famously the difficult structures.
This research has been developed based on the potential of the features in some applications than the statistical properties.
While, these features have been resolved the lip movement for AV letters recognition, Naive Bayesian and Red green blue and depth RGBD have been adopted for visual letter identification.
Naive Bayesian has 73.33% for usual recognition with three letters, each with ten frames, while RGBD classifier is 100% .
Within that for this case, two scenarios were made with different forms of noise placed on the face of normal, normal + 10% , normal + 25% and normal + 75% noise.
The first one trains and understands all classes, one after another.
While the other is training 95 percent of RGBD and 83.3 percent for Naive Bayesian with recognition of one of the inflicted forms.
RGBD identification is 100 percent for the second one, while 49.99 for the Naive Bayesian
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Ali, Wisam H.. 2021. A new method using naive bayes and RGBD facial identification based on extracted features from image pixels. Engineering and Technology Journal،Vol. 39, no. 4A, pp.632-641.
https://search.emarefa.net/detail/BIM-1281572
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Ali, Wisam H.. A new method using naive bayes and RGBD facial identification based on extracted features from image pixels. Engineering and Technology Journal Vol. 39, no. 4A (2021), pp.632-641.
https://search.emarefa.net/detail/BIM-1281572
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Ali, Wisam H.. A new method using naive bayes and RGBD facial identification based on extracted features from image pixels. Engineering and Technology Journal. 2021. Vol. 39, no. 4A, pp.632-641.
https://search.emarefa.net/detail/BIM-1281572
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references : p. 641
رقم السجل
BIM-1281572
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
تقوم هذه الخدمة بالتحقق من التشابه أو الانتحال في الأبحاث والمقالات العلمية والأطروحات الجامعية والكتب والأبحاث باللغة العربية، وتحديد درجة التشابه أو أصالة الأعمال البحثية وحماية ملكيتها الفكرية. تعرف اكثر