Literature DB >> 19369243

Quantitative assessment of perceived visibility enhancement with image processing for single face images: a preliminary study.

Ming Mei1, Susan J Leat.   

Abstract

PURPOSE: To develop a method to quantitatively assess the visibility enhancement of single face images gained with digital filters for people with maculopathy. To apply this method to obtaining preliminary results of visibility enhancement with subjectively preferred filters for people with maculopathy.
METHODS: Six subjects with normal vision and two with maculopathy were required to recognize seven facial expressions of single face images with different display durations of 2 seconds, 1 second, and 0.73 second. As a result, four facial expressions (anger, disgust, fear, and sadness) and a display duration of 0.73 second were chosen to measure single face image visibility enhancement with subjectively preferred digital filters. Finally, nine subjects with maculopathy viewed 30 images with four facial expressions that were either unfiltered or filtered with subjectively preferred digital filters. Each subject was required to identify the facial expression in a four-alternative, forced-choice paradigm. The errors with original and filtered images were calculated.
RESULTS: The method with four facial expressions and display duration of 0.73 second prevented a ceiling effect. The nine subjects with maculopathy made significantly fewer errors with the filtered images than with the original ones images (P = 0.004).
CONCLUSIONS: The developed method was effective in objective (quantitative) measurement of the enhancement in image visibility with digital filtering for people with maculopathy. There is a measurable improvement in facial expression recognition with subjectively preferred filters. The facial expression recognition task developed and validated in the present study is recommended as a method to be used in future studies of enhancement of face images.

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Year:  2009        PMID: 19369243     DOI: 10.1167/iovs.08-3079

Source DB:  PubMed          Journal:  Invest Ophthalmol Vis Sci        ISSN: 0146-0404            Impact factor:   4.799


  4 in total

Review 1.  High Tech Aids Low Vision: A Review of Image Processing for the Visually Impaired.

Authors:  Howard Moshtael; Tariq Aslam; Ian Underwood; Baljean Dhillon
Journal:  Transl Vis Sci Technol       Date:  2015-08-14       Impact factor: 3.283

2.  Visual search performance of patients with vision impairment: effect of JPEG image enhancement.

Authors:  Gang Luo; PremNandhini Satgunam; Eli Peli
Journal:  Ophthalmic Physiol Opt       Date:  2012-04-28       Impact factor: 3.117

3.  Effects of contour enhancement on low-vision preference and visual search.

Authors:  Premnandhini Satgunam; Russell L Woods; Gang Luo; P Matthew Bronstad; Zachary Reynolds; Chaithanya Ramachandra; Bartlett W Mel; Eli Peli
Journal:  Optom Vis Sci       Date:  2012-09       Impact factor: 1.973

4.  Characterization of field loss based on microperimetry is predictive of face recognition difficulties.

Authors:  Thomas S A Wallis; Christopher Patrick Taylor; Jennifer Wallis; Mary Lou Jackson; Peter J Bex
Journal:  Invest Ophthalmol Vis Sci       Date:  2014-01-07       Impact factor: 4.799

  4 in total

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