Asset Details
Do you wish to reserve the book?
Face Recognition Through Multi-Resolution Images
Hey, we have placed the reservation for you!
By the way, why not check out events that you can attend while you pick your title.
Oops! Something went wrong.
Looks like we were not able to place the reservation. Kindly try again later.
Are you sure you want to remove the book from the shelf?
Face Recognition Through Multi-Resolution Images
Do you wish to request the book?
Face Recognition Through Multi-Resolution Images
Please be aware that the book you have requested cannot be checked out. If you would like to checkout this book, you can reserve another copy
We have requested the book for you!
Your request is successful and it will be processed during the Library working hours. Please check the status of your request in My Requests.
Oops! Something went wrong.
Looks like we were not able to place your request. Kindly try again later.
Journal Article
Face Recognition Through Multi-Resolution Images
2022
Overview
In this paper, we introduce a new method for face recognition in multi-resolution images. The proposed method is composed of two phases: an off-line phase and an inference phase. In the off-line phase, we built the Kernel Partial Least Squares (KPLS) regression model to map the LR facial features to HR ones. The KPLS predictor was then used in the inference phase to map HR features from LR features. We applied in both phases the Block-Based Discrete Cosine Transform (BBDCT) descriptor to enhance the facial feature description. Finally, the identity matching was carried out with the K-Nearest Neighbor (KNN) classifier. Experimental study was conducted on the AR and ORL databases and the obtained results proved the efficiency of the proposed method to deal with LR and VLR face recognition problem.
Publisher
IGI Global
