Toni Kuparinen

Optimal Reconstruction of Approximate Planar Surfaces Using Photometric Stereo

Photometric stereo can be used to obtain a fast and noncontact surface reconstruction of Lambertian surfaces. Despite several published works concerning the uncertainties and optimal light configurations of photometric stereo, no solutions for optimal surface reconstruction from noisy real images have been proposed. In this paper, optimal surface reconstruction methods for approximate planar textured surfaces using photometric stereo are derived, given that the statistics of imaging errors are measurable. Simulated and real surfaces are experimentally studied, and the results validate that the proposed approaches improve the surface reconstruction especially for the high-frequency height variations.

Fractal dimension analysis and statistical processing of paper surface images towards surface roughness measurement

In this paper we present a method for optical paper surface roughness measurement, which overcomes the disadvantages of the traditional methods. Airflow-based roughness measurement methods and profilometer require expensive special equipment, essential laboratory conditions, are contact-based and slow and unsuitable for on-line control purposes methods. We employed an optical microscope with a built-in CCD-camera to take images of paper surface. The obtained image is considered as a texture. We applied statistical brightness measures and fractal dimension analysis for texture analysis. We have found a strong correlation between the roughness and a fractal dimension. Our method is non-contact–based, fast and is suitable for on-line control measurements in the paper industry.

Distance transforms on anisotropic surfaces for surface roughness measurement

The Distance Transform on Curved Space (DTOCS) calculates distances along a gray-level height map surface In this article, the DTOCS is generalized for surfaces represented as real altitude data in an anisotropic grid The distance transform combined with a nearest neighbor transform produces a roughness map showing the average roughness of image regions in addition to one roughness value for the whole surface The method has been tested on profilometer data measured on samples of different paper grades The correlation between the new method and the arithmetic mean deviation of the roughness surface, Sa, for small wavelengths was strong for all tested paper sample sets, indicating that the DTOCS measures small scale surface roughness.

On Surface Topography Reconstruction from Gradient Fields

In this paper, we propose and study surface reconstruction techniques for surfaces with high frequency height variation, which are common for example, in paper and textile manufacturing. Traditionally, photometric stereo methods have been developed and evaluated on objects with additive Gaussian noise. The minimization based methods may perform well on large objects, but they smooth the inherent high frequency variation of machined surfaces in the reconstruction. We extend a Fourier integration method with Wiener filter to reconstruct surfaces from two gradient fields. The experimental results validate that the proposed method performs well on surfaces with high frequency height variation.

Enhanced model for chromaticity differences

We have developed a model to calculate chromaticity differences from surfaces defined from the MacAdam ellipses in CIE 1931 (x,y)-chromaticity diagram. The idea is to transform the MacAdam ellipses to circles on planes and to connect these planes to each other as two surfaces through interpolation. The distances along the surfaces are calculated by a method based on the Weighted Distance Transform On Curved Space (WDTOCS). The chromaticity difference is calculated by combining the distances on the basis of the ellipse parametrization. The surface model corrects the planar values in chromaticity difference calculation. Our method can be applied to any set of planar ellipses.