Assessment of blurring and facial expression effects on facial image recognition

Mohamed Abdel-Mottaleb, Mohammad H. Mahoor

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations


In this paper we present methods for assessing the quality of facial images, degraded by blurring and facial expressions, for recognition. To assess the blurring effect, we measure the level of blurriness in the facial images by statistical analysis in the Fourier domain. Based on this analysis, a function is proposed to predict the performance of face recognition on blurred images. To assess facial images with expressions, we use Gaussian Mixture Models (GMMs) to represent images that can be recognized with the Eigenface method, we refer to these images as "Good Quality", and images that cannot be recognized, we refer to these images as "Poor Quality". During testing, we classify a given image into one of the two classes. We use the FERET and Cohn-Kanade facial image databases to evaluate our algorithms for image quality assessment. The experimental results demonstrate that the prediction function for assessing the quality of blurred facial images is successful. In addition, our experiments show that our approach for assessing facial images with expressions is successful in predicting whether an image has a good quality or poor quality for recognition. Although the experiments in this paper are based on the Eigenface technique, the assessment methods can be extended to other face recognition algorithms.

Original languageEnglish (US)
Title of host publicationAdvances in Biometrics - International Conference, ICB 2006, Proceedings
Number of pages7
StatePublished - Jun 15 2006
EventInternational Conference on Biometrics, ICB 2006 - Hong Kong, China
Duration: Jan 5 2006Jan 7 2006

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume3832 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


OtherInternational Conference on Biometrics, ICB 2006
CityHong Kong


  • Blurring Effect
  • Face recognition
  • Facial expressions
  • Gaussian Mixture Model
  • Image Quality Assessment

ASJC Scopus subject areas

  • Computer Science(all)
  • Biochemistry, Genetics and Molecular Biology(all)
  • Theoretical Computer Science


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