Keywords
RGBD, Bayesian-SVM, lips recognition, feature extraction
Document Type
Research Paper
Abstract
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.
Recommended Citation
H. Ali, Wisam
()
"A New Method Using Naive Bayes And RGBD Facial Identification Based on Extracted Features from Image Pixels,"
Engineering and Technology Journal: Vol. 39:
Iss.
4, Article 11.
DOI: https://doi.org/10.30684/etj.v39i4A.1936
DOI
10.30684/etj.v39i4A.1936
First Page
632
Last Page
641
