Picture of athlete cycling

Open Access research with a real impact on health...

The Strathprints institutional repository is a digital archive of University of Strathclyde's Open Access research outputs. Strathprints provides access to thousands of Open Access research papers by Strathclyde researchers, including by researchers from the Physical Activity for Health Group based within the School of Psychological Sciences & Health. Research here seeks to better understand how and why physical activity improves health, gain a better understanding of the amount, intensity, and type of physical activity needed for health benefits, and evaluate the effect of interventions to promote physical activity.

Explore open research content by Physical Activity for Health...

Removal of specular reflections from image sequences using feature correspondences

M. Z. Abbas Shah, Syed. and Marshall, Stephen and Murray, Paul (2017) Removal of specular reflections from image sequences using feature correspondences. Machine Vision and Applications, 28 (3). pp. 409-420. ISSN 0932-8092

[img] Text (Shah-etal-MVA2017-Removal-of-specular-reflections-from-image-sequences)
Shah_etal_MVA2017_Removal_of_specular_reflections_from_image_sequences.pdf - Accepted Author Manuscript
Restricted to Repository staff only until 2 February 2018.

Download (4MB) | Request a copy from the Strathclyde author

Abstract

The presence of specular highlights can hide underlying features of a scene within an image and can be problematic in many application scenarios. In particular, this poses a significant challenge for applications where image stitching is used to create a single static image of a scene from inspection footage of pipes, gas tubes, train tracks and concrete structures. Furthermore, they can hide small defects in the images causing them to be missed during inspection. We present a method which exploits additional information in neighbouring frames from video footage to reduce specularity from each frame. The technique first automatically determines frames which contain overlapping regions before the relationship that exists between them is exploited in order to suppress the effects of specular reflections. This results in an image that is free from specular highlights provided there is at least one frame present in the sequence where a given pixel is present in a diffuse form. The method is shown to work well on greyscale as well as colour images and effectively reduces specularity and significantly improves the quality of the stitched image, even in the presence of noise. While applied to the challenge of reducing specularity in inspection videos, the method improves upon the state-of-the-art in specularity removal, and, its applications are wider ranging as a general purpose pre-processing tool.