Design Issues for a Colour Photometric Stereo System

This paper presents the detailed performance analysis for a colour photometric stereo system proposed recently. The system recovers surface colour and surface normal for each surface patch separately, in the presence of highlights and shadows. The error analysis presented concerns every step of the algorithm, and it is based on the assumptions that errors may arise due to Gaussian image noise and errors in the accuracy with which the geometry of the illuminating set-up is known. The analysis is confirmed by experiments. The implications of this sensitivity analysis to the design of such a rig and the choice of threshold values for the algorithm are also discussed and recommendations to a designer are given.     

基于分形的从明暗恢复形状算法研究

从明暗恢复形状是计算机视觉领域中的经典病态问题，传统方法是通过引入光滑约束等条件来获得问题的解，但传统方法存在因过平滑而失真的缺点。针对传统方法恢复结果的局限性，提出了一种基于分形约束的从明暗恢复形状的新算法，该方法首先给出分形约束条件，之后结合反射图线性化与最小能量法来计算出曲面高度。该方法不仅克服了传统算法因基于光滑假设所造成的恢复结果过分平滑而失真的缺点，且不需要可积性的约束条件，也不需要对边界条件的假设，实验结果表明，该方法用于自然景物的三维表面重构，可获得比传统方法更好的恢复效果。     

Texture crack detection

Automatic visual inspection has become one of the active research issues in machine vision technology in the past decades. Most of the methodologies developed address the problems of defect detection on a nontextured or regularly textured surface. However, problems in detecting defects on a randomly textured surface, especially cracks, have not received much attention. In this paper, we present a novel algorithm that uses a Wigner model to identify cracks in complex textural backgrounds, regardless of whether the inspected surface is randomly or regularly textured. We also investigate the windowing characteristics of the Wigner distribution and their impact on crack detection. Some of the Brodatz' natural texture images have been used for evaluating the performance of the algorithm. Promising results are obtained and presented in this paper.     

Affine parameter estimation from the trace transform

In this paper, we assume that we are given the images of two segmented objects, one of which may be an affinely distorted version of the other, and wish to recover the values of the parameters of the affine transformation between the two images. The images may also differ by the overall level of illumination. The multiplicative constant of such difference may also be recovered. We present a generic theoretical framework to solve this problem. In terms of this framework, other proposed methods may be interpreted. We show how, in this framework, one can recover the affine parameters in a way that is robust to various effects, such as occlusion and illumination variation. The proposed method is generic enough to be applicable also to matching two images that do not depict the same scene or object.     

Edge postprocessing using probabilistic relaxation

In this paper, we develop the theory of probabilistic relaxation when the objects to be labeled are arranged in a rectangular grid with known adjacency relations. In this case a dictionary of permissible label configurations is available. The novelty of this work lies in the inclusion of measurements concerning binary relations between the objects to be labeled. These are compared with the corresponding binary relations between the nodes of the dictionary. This way, one of the major objections to probabilistic relaxation, namely, the disregard of the data after the initial assignment of probabilities, is removed. The theory we develop is demonstrated by applying it to the problem of edge relaxation labeling. We show that the inclusion of binary relations greatly improves the performance of algorithms of this kind and compare our approach with previously developed dictionary based approaches, both theoretically and experimentally. Also, a comparison with other edge-postprocessing strategies is provided.     

Mixture models with higher order moments

The authors present a novel method for mixed pixel classification where the classification of groups of mixed pixels is achieved by taking into consideration the higher order moments of the distributions of the pure and the mixed classes. The equations expressing the relationship between the higher order moments are used to augment the set of equations that express the relationship between the means only. The authors show that weighting these equations does not make the set of equations available less reliable. As a consequence, the number of equations can be increased and thus more classes than available bands can be identified. The method is exhaustively tested using simulated data and is also applied to real Landsat TM data for which ground data are available     

Automatic registration of ceramic tiles for the purpose of fault detection

An algorithm is presented for the automatic surface inspection of ceramic tiles for detection of faults in the deterministic patterns printed on them. The algorithm is based on the phase correlation method used to register the reference and test images. Received: 13 January 1997 / Accepted: 20 September 1999     

Classification of sets of mixed pixels with the hypothesis-testingHough transform

A new method is presented for mixed pixel classification where the classification of groups of mixed pixels is achieved by using the hypothesis-testing Hough transform. The motivation of the work is that some other estimation methods based on robust statistics, such as the standard Hough transform, have been criticised that, although they can cope with the presence of outliers, they give poor performance in the absence of outliers in comparison to the least-squares-error method. The method proposed in the paper is demonstrated using simulated data and proved to perform equally well in the presence and in the absence of outliers. It is also applied to real Landsat TM data