Abstract: A good face detection system should have the ability to identify objects with varying degrees of illumination and orientation. It should also be able to respond to all the possible variations in the image. The image of the face depends on the relative camera face pose such as the nose and one eye. The appearance of a face is directly influenced by the facial expression of a person and partially occluded by objects around it. One of the most important and necessary conditions for face recognition is to exclude the background of reliable face classification techniques. However, the face can appear in complex backgrounds and different positions. The face recognition system can mistake some areas of the background for faces. This paper solves some face recognition problems including segmenting, extracting and identifying facial features that are thought to face from the background.

Kausar Mia, Tariqul Islam, Md Assaduzzaman, Tajim Md. Niamat Ullah Akhund, Arnab Saha, Sonjoy Prosad Shaha, Md. Abdur Razzak and Angkur Dhar, “Parallelizing Image Processing Algorithms for Face Recognition on Multicore Platforms” International Journal of Advanced Computer Science and Applications(IJACSA), 13(11), 2022. http://dx.doi.org/10.14569/IJACSA.2022.0131193

@article{Mia2022,
title = {Parallelizing Image Processing Algorithms for Face Recognition on Multicore Platforms},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2022.0131193},
url = {http://dx.doi.org/10.14569/IJACSA.2022.0131193},
year = {2022},
publisher = {The Science and Information Organization},
volume = {13},
number = {11},
author = {Kausar Mia and Tariqul Islam and Md Assaduzzaman and Tajim Md. Niamat Ullah Akhund and Arnab Saha and Sonjoy Prosad Shaha and Md. Abdur Razzak and Angkur Dhar}
}