Skip to main content

Research Repository

Advanced Search

An improved photometric stereo through distance estimation and light vector optimization from diffused maxima region

Ahmad, Jahanzeb; Sun, Jiuai; Smith, Lyndon; Smith, Melvyn

An improved photometric stereo through distance estimation and light vector optimization from diffused maxima region Thumbnail


Jahanzeb Ahmad

Jiuai Sun

Lyndon Smith
Professor in Computer Simulation and Machine

Profile Image

Melvyn Smith
Research Centre Director Vision Lab/Prof


© 2013 Elsevier B.V. All rights reserved. Although photometric stereo offers an attractive technique for acquiring 3D data using low-cost equipment, inherent limitations in the methodology have served to limit its practical application, particularly in measurement or metrology tasks. Here we address this issue. Traditional photometric stereo assumes that lighting directions at every pixel are the same, which is not usually the case in real applications, and especially where the size of object being observed is comparable to the working distance. Such imperfections of the illumination may make the subsequent reconstruction procedures used to obtain the 3D shape of the scene prone to low frequency geometric distortion and systematic error (bias). Also, the 3D reconstruction of the object results in a geometric shape with an unknown scale. To overcome these problems a novel method of estimating the distance of the object from the camera is developed, which employs photometric stereo images without using other additional imaging modality. The method firstly identifies Lambertian diffused maxima region to calculate the object distance from the camera, from which the corrected per-pixel light vector is able to be derived and the absolute dimensions of the object can be subsequently estimated. We also propose a new calibration process to allow a dynamic(as an object moves in the field of view) calculation of light vectors for each pixel with little additional computation cost. Experiments performed on synthetic as well as real data demonstrates that the proposed approach offers improved performance, achieving a reduction in the estimated surface normal error of up to 45% as well as mean height error of reconstructed surface of up to 6 mm. In addition, when compared to traditional photometric stereo, the proposed method reduces the mean angular and height error so that it is low, constant and independent of the position of the object placement within a normal working range.


Ahmad, J., Sun, J., Smith, L., & Smith, M. (2014). An improved photometric stereo through distance estimation and light vector optimization from diffused maxima region. Pattern Recognition Letters, 50, 15-22.

Journal Article Type Article
Publication Date Dec 1, 2014
Deposit Date Sep 20, 2013
Publicly Available Date Apr 12, 2016
Journal Pattern Recognition Letters
Print ISSN 0167-8655
Publisher Elsevier
Peer Reviewed Peer Reviewed
Volume 50
Pages 15-22
Keywords photometric stereo, light vector calculation, distance
Public URL
Publisher URL
Related Public URLs
Additional Information Additional Information : Available online 19 September 2013 NOTICE: this is the author’s version of a work that was accepted for publication in Pattern Recognition Letters. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version will be published in Pattern Recognition Letters


You might also like

Downloadable Citations