R.E. Loke

The Sellaphora pupula species complex (Bacillariophyceae): morphometric analysis, ultrastructure and mating data provide evidence for five new species

Abstract Morphometric shape analysis and ultrastructural data are provided for six genodemes of the Sellaphora pupula species complex that have been studied during the last 20 years from Blackford Pond, Edinburgh, UK. The demes have previously been shown to be separated by prezygotic reproductive barriers: cells of different demes do not pair, though they may show residual interactions when sexualized. A new morphometric method, contour segment analysis, which was recently developed for diatoms in relation to automated identification, gives a clear separation of all six genodemes and indicates no heterogeneity within each. Legendre shape analysis gives less separation in this instance. All other available data, including molecular sequence data, also support separation of the six demes at species level. Five new species are therefore described: S. auldreekie, S. blackfordensis, S. capitata, S. lanceolata and S. obesa. The identity of S. pupula sensu stricto is clarified through designation of epitypes.

Volumetric processing of TOPAS underwater acoustic data

This paper describes the application of unsupervised volumetric reconstruction, segmentation and visualization techniques to underwater acoustic data for a 3D seabed analysis. New 3D interpolation and segmentation, methods are introduced and applied to both artificial and real seabed data. In the interpolation, all calculations are done in 3D. For the segmentation, a 3D to 2D simplification is described which yields more accurate results. The results show that the methods can be adequately used for a 3D seabed analysis.

Fast interpolation, segmentation and visualization of 3D sonar seabottom data by using tree structures

The authors describe an unsupervised processing pipeline for the analysis and visualization of sonar data. Recently developed 3D interpolation and segmentation methods are introduced, as well as a completely new surface construction method. All methods are based on employing quad- and octrees, which results in a fast processing. Accurate results are obtained for complex boundary shapes. Processed seabed data are accurately fused with bathymetric data. The methods enable a fast, highly accurate and interactive seabed analysis.

Diatom classification in ecological applications

We apply new contour features: (1) Point features by computing the convexity and curvature in small contour neighborhoods. (2) Segment features by segmenting the contour into convex, concave and straight segments, and computing length and curvature measures for each segment. (3) Global features by computing the mean, maximum and minimum of all point and segment features. Features can be extracted from noisy contours with convex, concave and straight parts, but also from completely convex ones, for the purpose of shape analysis or identification (ID) tasks. Using only four global features, a nearest-mean classifier yielded a perfect ID rate of 100% on diatoms with minute differences in shape, which are difficult to identify even for diatomists.

Diatom recognition by convex and concave contour curvature

We describe a new contour feature set. A contour is segmented into convex, concave and straight segments, after which length and curvature features are computed. A symmetry analysis allows the detection of the number of elementary segments. Results on two contour test sets were obtained: Using only four features, a simple nearest-mean classifier yielded a perfect identification (ID) rate of 100% on a small set consisting of shapes with minute differences, which are difficult to identify even for human experts. Using 10 features, it yielded 83.5% on a large set with very diverse shapes.

Quadtree-guided 3-D interpolation of irregular sonar data sets

Bottom-penetrating sonar can be used to visualize large areas, for example by normal logging and printing of collected pings. In many applications, it is necessary to obtain an impression of three-dimensional (3-D) structures, but this is not easy because of the irregular spatial sampling due to coarse ship trajectories. Normally, the ping map and the ping data, cover only a very small part of a region of interest. In this paper, we describe a new method for interpolating irregularly spaced sonar data. The basic idea is to use a two-dimensional quadtree of the ping map in order to guide the 3-D interpolation process: since gaps between pings become smaller at higher tree levels, the volume can be filled by marking neighborhood relations in the quadtree and interpolating available pings when they become neighbors. Different marking schemes and their central processing unit times are compared. In the interpolation process, we apply cross correlations of ping data in order to construct continuity of sloping reflections. Our results show that excellent results can be obtained on real sonar data sets, even for volumes filled for less than 7%, for which processing times are reasonable even for large areas, and that the interpolated data can be used for volumetric interactive visualization.

Sonar object visualization in an octree

The authors describe a new method for the detection and visualization of objects in 3D sonar data. The method has been applied to data obtained at a site which contains a well-defined target, being a buried tractor tire, sized 130 cm in diameter and 30 cm high. The surfaces of the corresponding sonar object have been accurately extracted using fast smoothing, filtering, segmentation and surface construction techniques. Analysis shows that the position of the target and the sonar object correctly coincide.

Segmentation of Range Images in a~Quadtree

We apply a fast segmenter to planar range images. By segmenting normal vectors of estimated planes in a quadtree, we can analyze very noisy data at high tree levels and guarantee interactivity in visualizing underlying 3D scenes. Techniques to enhance data at the original spatial resolution are given. Results on the ABW range dataset are better than those of several other segmenters.

Small CPU times and fast interactivity in sonar seabottom surveys

Sonar profiling of the seabottom provide 3D data sets that can cover huge survey areas with many gaps. We describe a multiresolution framework or visualization pipeline that is being optimized for dealing with such data, taking into account both the CPU time and the user interactivity. We describe the techniques employed: (a) the construction of a quadtree that allows to eliminate gaps by interpolating available 3D data, (b) a first but coarse visualization at a high tree level in order to rapidly change or adjust the region of interest, and (c) a very efficient triangulation (mesh reduction) that allows for a fast interactivity even at the highest detail level. By using one single octree, all processing can be combined because (1) gaps can be filled by interpolation since they are smaller at higher tree levels, and (2) connected components can be projected down the tree and refined using the data available there. As a result, huge data sets can be visualized in near realtime on normally-sized discrete grids using shading instead of wireframes, and this enables a fast searching for objects in the seabottom. Real CPU times are presented for a real sonar data set which is visualized at a low resolution, showing the overall shape of the seabottom, and at a high resolution, showing a (semi)buried pipeline. In order to detect an object at such a high resolution additional techniques are applied to the data: (a) an interslice interpolation in order to cope with the increased data sparseness and (b) a maximum-homogeneity filtering in order to cope with the decreased signal-to-noise-ratio. After the extraction of the pipeline a thinning technique is applied in order to be able to quantify its length.

Highlighting pipelines offshore Norway: visualization and quantitative analysis

Sonar profiler data of the seabottom are 3D data sets that can cover huge survey areas with many gaps. This paper describes a multiresolution visualization framework that is being optimized for dealing with such data taking into account both the CPU time and the user interactivity. The paper describes the techniques employed: (a) the construction of a quadtree that allows to eliminate gaps by interpolating available 3D data, (b) a first but coarse visualization at a high tree level in order to rapidly change or adjust the ROI, and (c) a very efficient triangulation (mesh reduction) that allows for a fast interactivity even at the highest detail level. By using one single octree all this processing can be combined because (1) gaps can be filled by interpolation because they are smaller at higher tree levels, (2) connected components can be projected down the tree and refined using the data available there and (3) triangulations at higher tree levels can be used to steer those at lower levels to fill efficiently large and smooth surface areas. As a result, huge data sets can be visualized in near realtime with OpenGL/VRML using shading instead of wireframes, and this enables a fast searching for objects in the seabottom. Real CPU times are presented for the visualization of a real sonar data set which was obtained in the North Sea, offshore Norway. These data are visualized at a low resolution, showing the overall shape of the seabottom, and at a high resolution, showing a (semi-)buried pipeline. In order to detect an object at such a high resolution additional techniques are applied to the data: (a) an interslice interpolation in order to cope with the increased data sparseness and (b) a maximum-homogeneity filtering in order to cope with the decreased SNR. After the extraction of the pipeline a thinning technique is applied in order to be able to quantify its length.