5 resultados para Sampling

em Universidad de Alicante


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We present an algorithm to process images of reflected Placido rings captured by a commercial videokeratoscope. Raw data are obtained with no Cartesian-to-polar-coordinate conversion, thus avoiding interpolation and associated numerical artifacts. The method provides a characteristic equation for the device and is able to process around 6 times more corneal data than the commercial software. Our proposal allows complete control over the whole process from the capture of corneal images until the computation of curvature radii.

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This correspondence presents an efficient method for reconstructing a band-limited signal in the discrete domain from its crossings with a sine wave. The method makes it possible to design A/D converters that only deliver the crossing timings, which are then used to interpolate the input signal at arbitrary instants. Potentially, it may allow for reductions in power consumption and complexity in these converters. The reconstruction in the discrete domain is based on a recently-proposed modification of the Lagrange interpolator, which is readily implementable with linear complexity and efficiently, given that it re-uses known schemes for variable fractional-delay (VFD) filters. As a spin-off, the method allows one to perform spectral analysis from sine wave crossings with the complexity of the FFT. Finally, the results in the correspondence are validated in several numerical examples.

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Light traps have been used widely to sample insect abundance and diversity, but their performance for sampling scarab beetles in tropical forests based on light source type and sampling hours throughout the night has not been evaluated. The efficiency of mercury-vapour lamps, cool white light and ultraviolet light sources in attracting Dynastinae, Melolonthinae and Rutelinae scarab beetles, and the most adequate period of the night to carry out the sampling was tested in different forest areas of Costa Rica. Our results showed that light source wavelengths and hours of sampling influenced scarab beetle catches. No significant differences were observed in trap performance between the ultraviolet light and mercury-vapour traps, whereas these two methods caught significantly more species richness and abundance than cool white light traps. Species composition also varied between methods. Large differences appear between catches in the sampling period, with the first five hours of the night being more effective than the last five hours. Because of their high efficiency and logistic advantages, we recommend ultraviolet light traps deployed during the first hours of the night as the best sampling method for biodiversity studies of those scarab beetles in tropical forests.

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The choice of sampling methods to survey saproxylic beetles is a key aspect to assessing conservation strategies for one of the most endangered assemblages in Europe. We evaluated the efficiency of three sampling methods: baited tube traps (TT), window traps in front of a hollow opening (WT), and emergence traps covering tree hollows (ET) to study richness and diversity of saproxylic beetle assemblages at species and family levels in Mediterranean woodlands. We also examined trap efficiency to report ecological diversity, and changes in the relative richness and abundance of species forming trophic guilds: xylophagous, saprophagous/saproxylophagous, xylomycetophagous, predators and commensals. WT and ET were similarly effective in reporting species richness and diversity at species and family levels, and provided an accurate profile of both the flying active and hollow-linked saproxylic beetle assemblages. WT and ET were the most complementary methods, together reporting more than 90 % of richness and diversity at both species and family levels. Diversity, richness and abundance of guilds were better characterized by ET, which indicates higher efficiency in outlining the ecological community of saproxylics that inhabit tree hollows. TT were the least effective method at both taxonomic levels, sampling a biased portion of the beetle assemblage attracted to trapping principles, however they could be used as a specific method for families such as Bostrichiidae, Biphyllidae, Melyridae, Mycetophagidae or Curculionidae Scolytinae species. Finally, ET and WT combination allows a better characterization of saproxylic assemblages in Mediterranean woodland, by recording species with different biology and linked to different microhabitat types.

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Since the beginning of 3D computer vision problems, the use of techniques to reduce the data to make it treatable preserving the important aspects of the scene has been necessary. Currently, with the new low-cost RGB-D sensors, which provide a stream of color and 3D data of approximately 30 frames per second, this is getting more relevance. Many applications make use of these sensors and need a preprocessing to downsample the data in order to either reduce the processing time or improve the data (e.g., reducing noise or enhancing the important features). In this paper, we present a comparison of different downsampling techniques which are based on different principles. Concretely, five different downsampling methods are included: a bilinear-based method, a normal-based, a color-based, a combination of the normal and color-based samplings, and a growing neural gas (GNG)-based approach. For the comparison, two different models have been used acquired with the Blensor software. Moreover, to evaluate the effect of the downsampling in a real application, a 3D non-rigid registration is performed with the data sampled. From the experimentation we can conclude that depending on the purpose of the application some kernels of the sampling methods can improve drastically the results. Bilinear- and GNG-based methods provide homogeneous point clouds, but color-based and normal-based provide datasets with higher density of points in areas with specific features. In the non-rigid application, if a color-based sampled point cloud is used, it is possible to properly register two datasets for cases where intensity data are relevant in the model and outperform the results if only a homogeneous sampling is used.