Face Recognition by CNN Using Hog and Bow Feature Extraction Approach - et. al., Dr. Manikandan, (Turkish Journal of Computer and Mathematics Education (TURCOMAT), 2021)
As we saw that there is a continuous development of Computer Vision and Artificial Intelligence, also we know that the Authentication play a vital role nowadays. And for this purpose Face is considered to be a most appropriate component. Face Recognition is technique that we use to compare the capture live or digital image from the stored image that we have in our database. Face Recognition is a technique which can easily contrived by intrinsic and extrinsic conditions. And in this situation we unable to get a desired result by using orthodox face recognition. This project helps us to recognize the face in any investigation department. In CNN, we can directly put the original image as an input which makes image processing quite simple. CNN perform 2-D transformation such as translation, Rotation and scaling. The overall approach is that we take a query image and divide the image into two set namely: Training image and tested image. On this image we apply BOW approach mainly used for feature Extraction. By feature extraction we remove all the unnecessary information and we get the output image in compact form which is compatible to our database (For example – Input Image = 64x64 reduces up-to 9x9). Put it into classifier for Recognition and after that we will get our recognized image.