Reconstruction of Lambertian Surfaces from Photometric Stereo
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Date
2005-06-13
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Abstract
The objective of this thesis is to implement and compare two algorithms to reconstruct the shape of an object from photometric stereo. Photometric stereo is a practical technique for determining an object's shape and surface reflectance properties at a distance. The implementation proposes the use of three images of an object, recorded from the same viewpoint but with different illumination. The first algorithm employs the Fourier transform method to solve the minimization problem. The gradient data is obtained by incorporating photometric stereo method on image triplets. The Fourier transform of the unknown surface is then expressed as a function of the Fourier transform of the gradients. The relative depth values are then obtained by applying an inverse Fourier transform of the function. The second algorithm is based on iterative reconstruction which minimizes the cost function by gradient descent and annealing. Both these algorithms are implemented to reconstruct both real and synthetic surfaces and the results are compared. It is also shown that better reconstruction results are obtained by adopting the second algorithm in the presence of discontinuities in the image. Noise sensitivity of the frequency-domain method is also evaluated. An experimental setup to obtain real world images is also presented.
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Reconstruction from Photometric Stereo, Mean Field Annealing, Iterative method, Fourier transform Method
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Degree
MS
Discipline
Electrical Engineering