Authors:
André Sobiecki
1
;
Alexandru Telea
1
;
Gilson Giraldi
2
;
Luiz Antonio Neves
3
and
Carlos Eduardo Thomaz
4
Affiliations:
1
University of Groningen, Netherlands
;
2
National Laboratory of Scientific Computation, Brazil
;
3
Paraná Federal University, Brazil
;
4
University Center of FEI, Brazil
Keyword(s):
Image Inpainting, Face Reconstruction, Statistical Decision, Image Quality Index.
Related
Ontology
Subjects/Areas/Topics:
Computer Vision, Visualization and Computer Graphics
;
Image and Video Analysis
;
Image Enhancement and Restoration
;
Image Formation and Preprocessing
;
Segmentation and Grouping
Abstract:
Facial images are often used in applications that need to recognize or identify persons. Many existing facial recognition tools have limitations with respect to facial image quality attributes such as resolution, face position, and artifacts present in the image. In this paper we describe a new low-cost framework for preprocessing low-quality facial images in order to render them suitable for automatic recognition. For this, we first detect artifacts based on the statistical difference between the target image and a set of pre-processed images in the database. Next, we eliminate artifacts by an inpainting method which combines information from the target image and similar images in our database. Our method has low computational cost and is simple to implement, which makes it attractive for usage in low-budget environments. We illustrate our method on several images taken from public surveillance databases, and compare our results with existing inpainting techniques.