Dense pixel matching between unrectified and distorted images using dynamic programming

In this paper, a novel framework for dense pixel matching based on dynamic programming is introduced. Unlike most techniques proposed in the literature, our approach assumes neither known camera geometry nor the availability of rectified images. Under such conditions, the matching task cannot be reduced to finding correspondences between a pair of scanlines. We propose to extend existing dynamic programming methodologies to a larger dimensional space by using a 3D scoring matrix so that correspondences between a line and a whole image can be calculated. After assessing our framework on a standard evaluation dataset of rectified stereo images, experiments are conducted on unrectified and non-linearly distorted images. Results validate our new approach and reveal the versatility of our algorithm.

Multiple Luminaire Identification in Airborne Images of Airport’s Approach Lighting Using Mathematical Morphology With Variable Length Structuring Element

The increasing demand for fast air transportation around the clock
has increased the number of night flights in civil aviation over
the past few decades. In night aviation, to land an aircraft, a
pilot needs to be able to identify an airport. The approach
lighting system (ALS) at an airport is used to provide
identification and guidance to pilots from a distance. ALS
consists of more than $100$ luminaires which are installed in a
defined pattern following strict guidelines by the International
Civil Aviation Organization (ICAO). ICAO also has strict
regulations for maintaining the performance level of the
luminaires. However, once installed, to date there is no automated
technique by which to monitor the performance of the lighting. We
suggest using images of the lighting pattern captured using a camera
placed inside an aircraft. Based on the information contained
within these images, the performance of the luminaires has to be
evaluated which requires identification of over $100$ luminaires
within the pattern of ALS image. This research proposes analysis
of the pattern using morphology filters which use a variable
length structuring element (VLSE). The dimension of the VLSE changes
continuously within an image and varies for different images.
A novel
technique for automatic determination of the VLSE is proposed and
it allows successful identification of the luminaires from the
image data as verified through the use of simulated and real data.

Premiere of "Spaced Images with Noise and Lines" Performance at the Joinery, Dublin, at at Spatial Music Collective concert. Authors: Lyon, E. Keywords: (Spatial Audio, Electroacoustic Music, Computer Music, Algorithmic Music) Publication date: 07 Oct 2011

Performance at the Joinery, Dublin, at at Spatial Music Collective concert

Red-shifts and red herrings in geographical ecology

I draw attention to the need for ecologists to take spatial structure into account more seriously in hypothesis testing. If spatial autocorrelation is ignored, as it usually is, then analyses of ecological patterns in terms of environmental factors can produce very misleading results. This is demonstrated using synthetic but realistic spatial patterns with known spatial properties which are subjected to classical correlation and multiple regression analyses. Correlation between an autocorrelated response variable and each of a set of explanatory variables is strongly biased in favour of those explanatory variables that are highly autocorrelated - the expected magnitude of the correlation coefficient increases with autocorrelation even if the spatial patterns are completely independent. Similarly, multiple regression analysis finds highly autocorrelated explanatory variables "significant" much more frequently than it should. The chances of mistakenly identifying a "significant" slope across an autocorrelated pattern is very high if classical regression is used. Consequently, under these circumstances strongly autocorrelated environmental factors reported in the literature as associated with ecological patterns may not actually be significant. It is likely that these factors wrongly described as important constitute a red-shifted subset of the set of potential explanations, and that more spatially discontinuous factors (those with bluer spectra) are actually relatively more important than their present status suggests. There is much that ecologists can do to improve on this situation. I discuss various approaches to the problem of spatial autocorrelation from the literature and present a randomisation test for the association of two spatial patterns which has advantages over currently available methods.

Geographical variation in total and inorganic arsenic content of polished (white) rice

An extensive data set of total arsenic analysis for 901 polished (white) grain samples, originating from 10 countries from 4 continents, was compiled. The samples represented the baseline (i.e., notspecifically collected from arsenic contaminated areas), and all were for market sale in major conurbations. Median total arsenic contents of rice varied 7-fold, with Egypt (0.04 mg/kg) and India (0.07 mg/kg) having the lowest arsenic content while the U.S. (0.25 mg/kg) and France (0.28 mg/kg) had the highest content. Global distribution of total arsenic in rice was modeled by weighting each country's arsenic distribution by that country's contribution to global production. A subset of 63 samples from Bangladesh, China, India, Italy, and the U.S. was analyzed for arsenic species. The relationship between inorganic arsenic contentversus total arsenic contentsignificantly differed among countries, with Bangladesh and India having the steepest slope in linear regression, and the U.S. having the shallowest slope. Using country-specific rice consumption data, daily intake of inorganic arsenic was estimated and the associated internal cancer risk was calculated using the U.S. Environmental Protection Agency (EPA) cancer slope. Median excess internal cancer risks posed by inorganic arsenic ranged 30-fold for the 5 countries examined, being 0.7 per 10,000 for Italians to 22 per 10,000 for Bangladeshis, when a 60 kg person was considered.

Temporal and geographical distribution of measles virus genotypes

The nucleotide sequence encoding the C terminus of the nucleocapsid protein of measles virus (MV) is the most variable in the genome. The sequence of this region is reported for 21 new MV strains and for virus RNA obtained from cases of subacute panencephalitis (SSPE) tissue. The nucleotide sequence of a total of 65 MV strains has been analysed using the CLUSTAL program to determine the relationships between the strains. An unrooted tree shows that eight different genotypes can be discerned amongst the sequences analysed so far. The data show that the C-terminal coding sequence of the nucleocapsid gene, although highly variable between strains, is stable in a given strain and does not appear to diverge in tissue culture. It therefore provides a good 'signature' sequence for specific genotypes. The sequence of this region can be used to discriminate new imported viruses from old 'endemic' strains of MV in a geographical area. The different genotypes are not geographically restricted although some appear to be the mainly 'endemic' types in large areas of the world. In global terms there appears to be at least four co-circulating genotypes of MV. The low level of divergence in the Edmonston lineage group isolated before 1970 indicates that some isolates are probably laboratory contaminants. This applies to some SSPE isolates such as the Halle, Mantooth and Horta-Barbosa strains as well as some wild-type isolates from that period.

Mapping Medieval Geographies: Geographical Encounters in the Latin West and Beyond, 300–1600

'Mapping Medieval Geographies' explores the ways in which geographical knowledge, ideas and traditions were formed in Europe during the Middle Ages. Leading scholars reveal the connections between Islamic, Christian, Biblical, and Classical geographical traditions from Antiquity to the later Middle Ages and Renaissance. The book is divided into two parts: Part I focuses on the notion of geographical tradition and charts the evolution of celestial and earthly geography in terms of its intellectual, visual and textual representations; whilst Part II explores geographical imaginations; that is to say, those 'imagined geographies' that came into being as a result of everyday spatial and spiritual experience. Bringing together approaches from art, literary studies, intellectual history and historical geography, this pioneering volume will be essential reading for scholars concerned with visual and textual modes of geographical representation and transmission, as well as the spaces and places of knowledge creation and consumption.

Profiling the ionome of rice and its use in discriminating geographical origins at the regional scale, China

Element profile was investigated for their use to trace the geographical origin of rice (Oryza sativa L.) samples. The concentrations of 13 elements (calcium (Ca), potassium (K), magnesium (Mg), phosphorus (P), boron (B), manganese (Mn), iron (Fe), nickel (Ni), copper (Cu), arsenic (As), selenium (Se), molybdenum (Mo), and cadmium (Cd)) were determined in the rice samples by inductively coupled plasma optical emission and mass spectrometry. Most of the essential elements for human health in rice were within normal ranges except for Mo and Se. Mo concentrations were twice as high as those in rice from Vietnam and Spain. Meanwhile, Se concentrations were three times lower in the whole province compared to the Chinese average level of 0.088 mg/kg. About 12% of the rice samples failed the Chinese national food safety standard of 0.2 mg/kg for Cd. Combined with the multi-elemental profile in rice, the principal component analysis (PCA), discriminant function analysis (DFA) and Fibonacci index analysis (FIA) were applied to discriminate geographical origins of the samples. Results indicated that the FIA method could achieve a more effective geographical origin classification compared with PCA and DFA, due to its efficiency in making the grouping even when the elemental variability was so high that PCA and DFA showed little discriminatory power. Furthermore, some elements were identified as the most powerful indicators of geographical origin: Ca, Ni, Fe and Cd. This suggests that the newly established methodology of FIA based on the ionome profile can be applied to determine the geographical origin of rice.

Weathering rinds as mirror images of palaeosols: Examples from the Western Alps with correlation to Antarctica and Mars

Weathering rinds have been used for decades as relative age indicators to differentiate glacial deposits in long Quaternary sequences, but only recently has it been shown that rinds contain long and extensive palaeoenvironmental records that often extend far beyond mere repositories of chemical weathering on both Earth and Mars. When compared with associated palaeosols in deposits of the same age, rinds often carry a zonal weathering record that can be correlated with palaeosol horizon characteristics, with respect to both abiotic and biotic parameters. As demonstrated with examples from the French and Italian Alps, rinds in coarse clastic sediment contain weathering zones that correlate closely with horizon development in associated palaeosols of presumed Late Glacial age. In addition to weathering histories in both rinds and palaeosols, considerable evidence exists to indicate that the black mat impact (12.8 ka) reached the European Alps, a connection with the Younger Dryas readvance supported by both mineral and chemical composition. Preliminary metagenomic microbial analysis using density gradient gel electrophoresis suggests that the eubacterial microbial population found in at least one Ah palaeosol horizon associated with a rind impact site is different from that in other Late Glacial and Younger Dryas surface palaeosol horizons. © 2013 The Geological Society of London.