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Reseach Article

Shape Reconstruction of Fracture Surface for HSLA Materials using Photometric-Stereo Images

Published on October 2011 by Mohan P. Pradhan, Ratika Pradhan, M. K. Ghose
International Symposium on Devices MEMS, Intelligent Systems & Communication
Foundation of Computer Science USA
ISDMISC - Number 9
October 2011
Authors: Mohan P. Pradhan, Ratika Pradhan, M. K. Ghose
6b390cb8-4991-4fc2-96fe-df413f627432

Mohan P. Pradhan, Ratika Pradhan, M. K. Ghose . Shape Reconstruction of Fracture Surface for HSLA Materials using Photometric-Stereo Images. International Symposium on Devices MEMS, Intelligent Systems & Communication. ISDMISC, 9 (October 2011), 13-18.

@article{
author = { Mohan P. Pradhan, Ratika Pradhan, M. K. Ghose },
title = { Shape Reconstruction of Fracture Surface for HSLA Materials using Photometric-Stereo Images },
journal = { International Symposium on Devices MEMS, Intelligent Systems & Communication },
issue_date = { October 2011 },
volume = { ISDMISC },
number = { 9 },
month = { October },
year = { 2011 },
issn = 0975-8887,
pages = { 13-18 },
numpages = 6,
url = { /proceedings/isdmisc/number9/3781-isdm194/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Proceeding Article
%1 International Symposium on Devices MEMS, Intelligent Systems & Communication
%A Mohan P. Pradhan
%A Ratika Pradhan
%A M. K. Ghose
%T Shape Reconstruction of Fracture Surface for HSLA Materials using Photometric-Stereo Images
%J International Symposium on Devices MEMS, Intelligent Systems & Communication
%@ 0975-8887
%V ISDMISC
%N 9
%P 13-18
%D 2011
%I International Journal of Computer Applications
Abstract

Shape from photometric stereo images is a method of constructing 3D shape of a 2D image of any scene using its multiple images. It recovers shape from multiple images of the same scene generated using a fixed viewing direction and the different light source direction. In this work we have considered only two images- left image and right image of fracture surface of High Speed Low Alloy (HSLA) material. The images used in this paper are captured using Scanning Electron Microscopes (SEMs). We have presented a very simple approach to recover the shape form photometric stereo-images -using features matching algorithm.

References
  1. [<ol> Ruo Zhang, Ping-Sing Tsai, James Edwin Cryer, Mubarak Shah, “Shape from Shading: A Survey”, IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 21, No. 8, pp 690-706, 1999. K. Ikeuchi and B.K.P. Horn, "Numerical shape from shading and occluding boundaries", Artificial Intelligence, Vol. 17, No. 1-3, pp. 141-184, 1981. M. J. Brooks and B. K. P. Horn, "Shape and source from shading", in proceedings of International Joint Conference on Artificial Intelligence, pp. 932-936, 1985. R. T. Frankot and R. Chellappa, "A method for enforcing integrability in shape from shading algorithms", IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol 10, pp. 439-451, 1988. B. K. P. Horn, "Shape from Shading: A Method for Obtaining the Shape of a Smooth Opaque Object from One View", PhD thesis, MIT, 1970. B. K. P. Horn, "Height and gradient from shading", International Journal of Computer Vision, pp. 37-75, 1989. M. Bichsel and A. P. Pentland, "A simple algorithm for
Index Terms

Computer Science
Information Sciences

Keywords

Shape-from-shading (SFS) Stereo-image gradients laplacian tilt angle depth