Spherical harmonics descriptor for 2D-image retrieval

In this paper, spherical harmonics are proposed as shape descriptors for 2D images. We introduce the concept of connectivity; 2D images are decomposed using connectivity, which is followed by 3D model construction. Spherical harmonics are obtained for 3D models and used as descriptors for the underlying 2D shapes. Difference between two images is computed as the Euclidean distance between their spherical harmonics descriptors. Experiments are performed to test the effectiveness of spherical harmonics for retrieval of 2D images. Item S8 within the MPEG-7 still images content set is used for performing experiments; this dataset consists of 3621 still images. Experimental results show that the proposed descriptors for 2D images are effective

A composite descriptor for shape retrieval

In this paper, a composite descriptor for shape retrieval has been proposed. The proposed descriptor is obtained from Generic Fourier Descriptors (GFD) for the shape region and the shape contour. A composite descriptor derived from GFD of the shape region and the shape contour is used for indexing and retrieval of shapes. Difference between two images is computed as the Euclidean distance between their composite descriptors. Experiments are performed to test the effectiveness of the proposed descriptor for retrieval of 2d images. Sets of composite descriptors, obtained by assigning different weights to the region component and the contour component, are also evaluated. Item S8 within the MPEG-7 Still Images Content Set is used for performing experiments; this dataset consists of 3621 still images. Experimental results show that the proposed descriptor is effective.

Connectivity-based shape descriptors

In this paper, we propose a method for indexing and retrieval of images based on shapes of objects. The concept of connectivity is introduced. 3D models are used to represent 2D images. 2D images are decomposed a priori using connectivity which is followed by 3D model construction. 3D model descriptors are obtained for 3D models and used to represent the underlying 2D shapes. We have used spherical harmonics descriptors as the 3D model descriptors. Difference between two images is computed as the Euclidean distance between their descriptors. Experiments are performed to test the effectiveness of spherical harmonics for retrieval of 2D images. The proposed method is compared with methods based on principal components analysis (PCA) and generic Fourier descriptors (GFD). It is found that the proposed method is effective. Item S8 within the MPEG-7 still images content set is used for performing experiments.

Habitat suitability for marine fishes using presence-only modelling and multibeam sonar

Improved access to multibeam sonar and underwater video technology is enabling scientists to use spatially-explicit, predictive modelling to improve our understanding of marine ecosystems. With the growing number of modelling approaches available, knowledge of the relative performance of different models in the marine environment is required. Habitat suitability of 5 demersal fish taxa in Discovery Bay, south-east Australia, were modelled using 10 presence-only algorithms: BIOCLIM, DOMAIN, ENFA (distance geometric mean [GM], distance harmonic mean [HM], median [M], area-adjusted median [Ma], median + extremum [Me], area-adjusted median + extremum [Mae] and minimum distance [Min]), and MAXENT. Model performance was assessed using kappa and area under curve (AUC) of the receiver operator characteristic. The influence of spatial range (area of occupancy) and environmental niches (marginality and tolerance) on modelling performance were also tested. MAXENT generally performed best, followed by ENFA-GM and -HM, DOMAIN, BIOCLIM, ENFA-M, -Min, -Ma, -Mae and -Me algorithms. Fish with clearly definable niches (i.e. high marginality) were most accurately modelled. Generally, Euclidean distance to nearest reef, HSI-b (backscatter), rugosity and maximum curvature were the most important variables in determining suitable habitat for the 5 demersal fish taxa investigated. This comparative study encourages ongoing use of presence-only approaches, particularly MAXENT, in modelling suitable habitat for demersal marine fishes.

Unleashing the vermin : vectored route-length minimization

We have posed a simple but interesting graph theoretic problem and posited a heuristic solution procedure, which we have christened as Vectored Route-length Minimization (VeRMin). Basically, it constitutes a re-casting of the classical “shortest route” problem in a strictly Euclidean space. We have presented only a heuristic solution process hoping that a formal proof will eventually emerge as the problem receives wider exposure within mathematical circles.

An unified framework based on p-norm for feature aggregation in content- based image retrieval

Feature aggregation is a critical technique in content- based image retrieval systems that employ multiple visual features to characterize image content. In this paper, the p-norm is introduced to feature aggregation that provides a framework to unify various previous feature aggregation schemes such as linear combination, Euclidean distance, Boolean logic and decision fusion schemes in which previous schemes are instances. Some insights of the mechanism of how various aggregation schemes work are discussed through the effects of model parameters in the unified framework. Experiments show that performances vary over feature aggregation schemes that necessitates an unified framework in order to optimize the retrieval performance according to individual queries and user query concept. Revealing experimental results conducted with IAPR TC-12 ImageCLEF2006 benchmark collection that contains over 20,000 photographic images are presented and discussed.

Shifting ground in some Australian photography

This is a report of a practice-as-research project. The chapter outlines McArdle's discoveries of means by which the pre-conscious processes of binocular vision and steropsis can be made visible in an effect which with one-eyed vision renders the scene 3-dimensional.

In the book's introduction editor Mehigan writes "[The] will to creation is only assayable once we estimate the role of the observer in the construction of space. McArdle's contribution, in engaging with the question of the animating presence of the observer focuses not just on what is caught in the lens of the photographer at the moment of depiction, but how the photographer's movement through space is the 'force field' that insinuates itself into the landscape and enters into a reciprocal relationship with it. The schematism of Euclidean geometry, for this reason, cannot account for the truth of the photographer's images; McArdle's metaphors are singularly non-Euclidean in their description of how objects are held together in the imaginative space of mental awareness."

A two stage vector quantization approach via self-organizing map

In this paper, a two-stage algorithm for vector quantization is proposed based on a self-organizing map (SOM) neural network. First, a conventional self-organizing map is modified to deal with dead codebooks in the learning process and is then used to obtain the codebook distribution structure for a given set of input data. Next, subblocks are classified based on the previous structure distribution with a prior criteria. Then, the conventional LBG algorithm is applied to these sub-blocks for data classification with initial values obtained via the SOM. Finally, extensive simulations illustrate that the proposed two-stage algorithm is very effective.

Beyond the topological map : developing alternate mappings in self organisation

The self organising map is a well established unsupervised
learning technique which is able to form sophisticated representations of an input data set. However, conventional Self Organising Map (SOM) algorithms are limited to the production of topological maps — that is, maps where distance between points on the map have a direct relationship to the Euclidean distance between the training vectors corresponding to those points.

It would be desirable to be able to create maps which form clusters on primitive attributes other than Euclidean distance; for example, clusters based upon orientation or shape. Such maps could provide a novel approach to pattern recognition tasks by providing a new method to associate groups of data.

In this paper, it is shown that the type of map produced by SOM algorithms is a direct consequence of the lateral connection strategy employed. Given this knowledge, a technique is required to establish the feasability of using an alternative lateral connection strategy. Such a technique is presented. Using this technique, it is possible to rule out lateral connection strategies that will not produce output states useful to the organisation process. This technique is demonstrated using conventional Laplacian interconnection as well as a number of novel interconnection strategies.

Does the choice of neighbourhood supermarket access measure influence associations with individual-level fruit and vegetable consumption? A case study from Glasgow

Background
Previous studies have provided mixed evidence with regards to associations between food store access and dietary outcomes. This study examines the most commonly applied measures of locational access to assess whether associations between supermarket access and fruit and vegetable consumption are affected by the choice of access measure and scale.

Method
Supermarket location data from Glasgow, UK (n = 119), and fruit and vegetable intake data from the 'Health and Well-Being' Survey (n = 1041) were used to compare various measures of locational access. These exposure variables included proximity estimates (with different points-of-origin used to vary levels of aggregation) and density measures using three approaches (Euclidean and road network buffers and Kernel density estimation) at distances ranging from 0.4 km to 5 km. Further analysis was conducted to assess the impact of using smaller buffer sizes for individuals who did not own a car. Associations between these multiple access measures and fruit and vegetable consumption were estimated using linear regression models.

Results
Levels of spatial aggregation did not impact on the proximity estimates. Counts of supermarkets within Euclidean buffers were associated with fruit and vegetable consumption at 1 km, 2 km and 3 km, and for our road network buffers at 2 km, 3 km, and 4 km. Kernel density estimates provided the strongest associations and were significant at a distance of 2 km, 3 km, 4 km and 5 km. Presence of a supermarket within 0.4 km of road network distance from where people lived was positively associated with fruit consumption amongst those without a car (coef. 0.657; s.e. 0.247; p0.008).

Conclusions
The associations between locational access to supermarkets and individual-level dietary behaviour are sensitive to the method by which the food environment variable is captured. Care needs to be taken to ensure robust and conceptually appropriate measures of access are used and these should be grounded in a clear a priori reasoning.

Does parkland influence walking? The relationship between area of parkland and walking trips in Melbourne, Australia

Background : Using two different measures of park area, at three buffer distances, we sought to investigate the ways in which park area and proximity to parks, are related to the frequency of walking (for all purposes) in Australian adults. Little previous research has been conducted in this area, and results of existing research have been mixed.

Methods : Residents of 50 urban areas in metropolitan Melbourne, Australia completed a physical activity survey (n = 2305). Respondents reported how often they walked for >=10 minutes in the previous month. Walking frequency was dichotomised to 'less than weekly' (less than 1/week) and 'at least weekly' (1/week or more). Using Geographic Information Systems, Euclidean buffers were created around each respondent's home at three distances: 400metres (m), 800 m and 1200 m. Total area of parkland in each person's buffer was calculated for the three buffers. Additionally, total area of 'larger parks', (park space >= park with Australian Rules Football oval (17,862 m2)), was calculated for each set of buffers. Area of park was categorised into tertiles for area of all parks, and area of larger parks (the lowest tertile was used as the reference category). Multilevel logistic regression, with individuals nested within areas, was used to estimate the effect of area of parkland on walking frequency.

Results : No statistically significant associations were found between walking frequency and park area (total and large parks) within 400 m of respondent's homes. For total park area within 800 m, the odds of walking at least weekly were lower for those in the mid (OR 0.65, 95% CI 0.46-0.91) and highest (OR 0.65, 95% CI 0.44-0.95) tertile of park area compared to those living in areas with the least amount of park area. Similar results were observed for total park area in the 1200 m buffers. When only larger parks were investigated, again more frequent walking was less likely when respondents had access to a greater amount of park area.

Conclusions : In this study we found that more park area in residential environments reduced the odds of walking more frequently. Other area characteristics such as street connectivity and destinations may underlay these associations by negatively correlating with park area.