An Automatic Framework for Segmentation and Digital Inpainting of 2D Frontal Face Images
Nowadays applications that use face images as input for people identification have been very common. In general, the input image must be preprocessed in order to fit some normalization and quality criteria. In this paper, we propose a computational framework composed of digital image quality computa...
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Published in: | Revista IEEE América Latina Vol. 10; no. 6; pp. 2263 - 2272 |
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Main Authors: | , , , |
Format: | Journal Article |
Language: | English |
Published: |
Los Alamitos
IEEE
01-12-2012
The Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Subjects: | |
Online Access: | Get full text |
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Summary: | Nowadays applications that use face images as input for people identification have been very common. In general, the input image must be preprocessed in order to fit some normalization and quality criteria. In this paper, we propose a computational framework composed of digital image quality computation, segmentation of the damaged regions on face images by statistical decision, morphological operators and image restoration by inpainting techniques. Additionally, in this work we propose a new method for digital inpainting that considers as relevant information for such restoration the neighboring pixel intensities as well as prior information extracted from an image database. To assess the efficiency of the computational framework proposed, we have used 2D face images from public databases. The results show that our inpainting method performs similarly to the traditional ones on quasi-homogeneous regions and gives better results when the damaged areas includes complex image patterns. |
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Bibliography: | ObjectType-Article-2 SourceType-Scholarly Journals-1 ObjectType-Feature-1 content type line 23 |
ISSN: | 1548-0992 1548-0992 |
DOI: | 10.1109/TLA.2012.6418131 |