Browsing by Author "Vidal, R"

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    A real time visual sensor for supervision of flotation cells
    (PERGAMON-ELSEVIER SCIENCE LTD, 1998) Cipriano, A; Guarini, M; Vidal, R; Soto, A; Sepulveda, C; Mery, D; Briseno, H
    This paper describes an expert system for the supervision of flotation plants based on ACEFLOT, a real time analyzer of the characteristics of the froth that is formed on.:the surface of flotation cells. The ACEFLOT analyzer is based on image processing and measures several physical variables of the froth, including colorimetric, geometric and dynamic information. On the other hand, the expert system detects abnormal operation states and suggests corrective actions, supporting operators on the supervision and control of the flotation plant. (C) 1998 Published by Elsevier Science Ltd. All rights reserved.
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    Enhanced DNA extraction and PCR amplification of SSU ribosomal genes from crustose coralline algae
    (2002) Vidal, R; Meneses, I; Smith, M
    As crustose Corallinales on the coasts of Chile are usually flat, thin, strongly adherent to the rocks and with a high concentration of polysaccharides, there is a need to improve DNA extraction for molecular studies. The paper describes a protocol to achieve this, which includes steps for disruption of cell walls and precipitation of polysaccharides and proteins; this leads to a PCR-quality product. The DNA obtained permitted amplification of SSU and rbcL genes from small amounts of material (< 1 g) of several genera and species of Corallinales. Comparison of the sequences of small SSU fragments (approximately 500 bp), combined with morphological characters, together provide sufficient resolution to distinguish organisms at the genus and species levels.
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    Segmentation of circular casting defects using a robust algorithm
    (BRITISH INST NON-DESTRUCTIVE TESTING, 2005) Ghoreyshi, A; Vidal, R; Mery, D
    In this paper, we describe three methods for detecting defects in cast aluminium using X-radioscopic images. The first method is based on the assumption that most defects have the shape of a circular high-intensity spot. Therefore, defects are detected using a template matching-like algorithm. This method works well when the defects are far enough from the edges of the major shapes in the image, and when the image gives a closer view of the defect. The second method deals with the defects which are closer to the edges in the image, and therefore are missed by the first method. This method distinguishes between defects and edges by using the following properties of a defect: they are local maxima of the image intensity, and the distribution of the intensity in a patch around the defect should resemble more that of a corner than that of an edge. Both local maxima and corner-like properties are computed using the second order derivatives of the image intensities, and the Harris Corner Detector algorithm. The third algorithm is a simple combination of the aforementioned methods in which a pixel is considered to be a defect if it is detected as a defect by either of the two methods. We present experiments using the third method showing that 94.3% of the defects are correctly detected, with only 1.3 false alarms per image.
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    Tracking of points in a calibrated and noisy image sequence
    (2004) Mery Quiroz, Domingo Arturo; Ochoa, F; Vidal, R; Campilho, A; Kamel, M