This work presents a new efficient method for fitting ellipses to scattered data. Previous algorithms either fitted general conics or were computationally expensive. By minimizing the algebraic distance subject to the constraint 4acb 2 = 1, the new method incorporates the ellipticity constraint into the normalization factor. The proposed method combines several advantages: It is ellipse-specific, so that even bad data will always return an ellipse. It can be solved naturally by a generalized eigensystem. It is extremely robust, efficient, and easy to implement.

A methodology for {evaluating range image segmentation algorithms is proposed. This methodology involves 1) a common set of 40 laser range finder images and 40 structured light scanner images that have manually specified ground truth and 2) a set of defined performance metrics for instances of correctly segmented, missed, and noise regions, over-and undersegmentation, and accuracy of the recovered geometry. A tool is used to objectively-compare a machine generated segmentation against the specified ground truth. Four research groups have contributed to evaluate their own algorithm for segmenting a range image into planar patches. Index Terms-Experimental comparison of algorithms, range image segmentation, low level processing, performance evaluation In general, standardized segmentation error metrics are needed to kelp advance the state-of-the-art. No quantitative metrics are measured on standard test images in most of today's research environments.

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In this paper we evaluate several methods of fitting data to conic sections. Conic fitting is a commonly required task in machine vision, but many algorithms perform badly on incomplete or noisy data. We evaluate several algorithms under various noise and degeneracy conditions, identify the key parameters which affect sensitivity, and present the results of comparative experiments which emphasize the algorithms' behaviours under common examples of degenerate data. In addition, complexity analyses in terms of flop counts are provided in order to further inform the choice of algorithm for a specific application.

Mayan crude, residuum, and hydrocracked asphaltenes have been separated into two fractions by extended Soxhlet extraction in n-heptane. Although the solubility, composition, and molecular structures differ slightly, the greatest difference between the two asphaltene fractions is the degree to which they associate in solution. The vapor-phase osmometry molecular weight, molecular size by size-exclusion chromatography, and small-angle neutron scattering indicate that approximately 25% of Mayan asphaltene is not highly associated in aromatic solvents and, thus, is noncolloidal. By contrast, the remaining asphaltene forms large, rodlike colloidal particles in solution and has a higher apparent molecular weight. Although laser desorption mass spectrometry indicates that the molecular weight of the individual molecules in maltenes and asphaltenes is not very different, high-resolution mass spectrometry indicates that the size of the aromatic core of asphaltenes is significantly larger than those in maltenes. Furthermore, the tendency of the residuum fractions to form coke during thermal cracking is likely related to the size of the largest polyaromatic rings.

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