A multi-classifier approach to face image segmentation for travel documents

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.

► We propose a face image segmentation approach for machine readable travel documents. ► The image segmentation is exploited for the automatic quality check of photographs. ► A multi-classifier architecture is proposed, based on color and texture information. ► Extensive tests on image segmentation and quality check have been carried out. ► Quality check accuracy higher than that of commercial systems is reached.