Evaluación de la calidad de las imágenes de rostros utilizadas para la identificación de las personas

Face Image Quality Evaluation for Person Identification

Heydi Méndez-Vázquez, Leonardo Chang, Dayron Rizo-Rodríguez y Annette Morales-González

Centro de Aplicaciones de Tecnologías de Avanzadas (CENATAV), La Habana, Cuba hmendez@cenatav.co.cu, lchang@cenatav.co.cu, drizo@cenatav.co.cu, amorales@cenatav.co.cu

Artículo recibido el 17/02/2011.
Aceptado el 21/10/2011.

Resumen

La evaluación automática de la calidad de las imágenes de rostros es un tema de gran importancia dentro del desarrollo de sistemas biométricos de reconocimiento de rostros. En este trabajo, se describe un esquema para evaluar si las imágenes de rostros cumplen los parámetros establecidos en la norma ISO/IEC 19794-5, que determinan si tienen valor identificativo y si pueden ser utilizadas en documentos de identificación personal. Se presentan nuevos algoritmos para el análisis de las imágenes y la clasificación de estas respecto a los parámetros que se evalúan en el esquema propuesto. El esquema propuesto se implementa en una biblioteca de vínculos dinámicos (DLL) que brinda ventajas para su uso en diferentes aplicaciones. Se evalúa la propuesta con imágenes de buena y mala calidad y se muestra de manera experimental, la factibilidad de su uso.

Palabras clave. Reconocimiento de rostros, evaluación de la calidad, estándares, procesamiento de imágenes.

Abstract

Automatic evaluation of face image quality is an important topic in the development of face recognition systems. This paper describes a framework for assessing the conformity of face images with the parameter set in the standard ISO/IEC 19794-5 that determines if given images possess an identification value and can be used in personal identification documents. New algorithms for image analysis and image classification with respect to parameters evaluated in the proposed framework are presented. The proposal is implemented as a dynamic link library (DLL), offering many advantages for the use in different applications. Good and bad quality images are evaluated, and the feasibility of the use of this framework is shown experimentally.

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