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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Bibliographic Details
Published in:Revista IEEE América Latina Vol. 10; no. 6; pp. 2263 - 2272
Main Authors: Sobiecki, A., Giraldi, G. A., Neves, L. A. P., Thomaz, C. E.
Format: Journal Article
Language:English
Published: Los Alamitos IEEE 01-12-2012
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
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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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ISSN:1548-0992
1548-0992
DOI:10.1109/TLA.2012.6418131