The FERET Evaluation Methodology for Face-Recognition Algorithms
IEEE Transactions on Pattern Analysis and Machine Intelligence
Face Detection in Color Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
EMMCVPR '99 Proceedings of the Second International Workshop on Energy Minimization Methods in Computer Vision and Pattern Recognition
Multispectral Texture Analysis Using Interplane Sum- and Difference-Histograms
Proceedings of the 24th DAGM Symposium on Pattern Recognition
An efficient boosting algorithm for combining preferences
The Journal of Machine Learning Research
Overview of the Face Recognition Grand Challenge
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01
Saliency model-based face segmentation and tracking in head-and-shoulder video sequences
Journal of Visual Communication and Image Representation
Expert system segmentation of face images
Expert Systems with Applications: An International Journal
Evaluating Systems Assessing Face-Image Compliance with ICAO/ISO Standards
Biometrics and Identity Management
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
A compositional exemplar-based model for hair segmentation
ACCV'10 Proceedings of the 10th Asian conference on Computer vision - Volume Part III
Face segmentation using skin-color map in videophone applications
IEEE Transactions on Circuits and Systems for Video Technology
Hi-index | 12.05 |
The adoption of face images in machine readable travel documents requires some quality constraints to be fulfilled (e.g., no flash reflections on skin or hair across eyes), as specified in the ISO/IEC 19794-5 standard. Automatically evaluating the compliance of a face image to such requirements needs a precise knowledge of the image structure, intended as the partitioning of the image into its main components (face, hair, clothes and background regions). In this paper a multi-classifier system based on color and texture information is proposed for face image segmentation. Extensive experiments carried out both on the segmentation algorithm and on its application to ISO/IEC 19794-5 standard compliance verification are reported and discussed. The results obtained are encouraging and confirm that: (i) the robustness of the proposed segmentation approach to deal with difficult image characteristics (e.g., uneven illumination or varied background) is satisfactory and (ii) the knowledge deriving from image segmentation is very useful for ISO/IEC 19794-5 standard compliance verification.