60 resultados para fractal descriptors

em Deakin Research Online - Australia


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A method is described for making rapid in situ field measurements of riverbed topography over spatial scales of ≅1–10 m. This method uses rolling balls to make quick, accurate measurements of river-bed roughness at several spatial scales. Random sampling and replication generate multiple estimates of the fractal dimension (d) that can be used to test for significant differences in the complexity of riverbed architecture between habitat types and spatial scales.

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Generic Fourier Descriptors have been used for image retrieval [12]. In this paper, we have proposed a modification to the Generic Fourier Descriptors. We have performed experiments to compare the performance of the proposed method with the standard method. Tests were performed on Set B of the MPEG-7 Still Images Content Set [13]. The experimental results show the effectiveness of the proposed method.

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We propose a method for enhancing the accuracy of shape descriptors. The concept of connectivity to obtain discriminating shape descriptors, is introduced. We show how connectivity is applied to two popular shape descriptors. Experiments are performed to test the effect of using connectivity with generic Fourier descriptors and distance histograms. Item S8 within the MPEG-7 still images content set is used for performing experiments. This dataset consists of 3621 still images. The experimental results show that connectivity enhances the performance of the methods significantly.

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This paper presents a new kind of image retrieval system which obtains the feature vectors of images by estimating their fractal dimension; and at the same time establishes a tree-structure image database. After preprocessing and feature extracting, a given image is matched with the standard images in the image database using a hierarchical method of image indexing.

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Background The aim of this study was to identify specific bone characteristics of stress fracture (SF) cases in sportswomen. To date, no tool is able to distinguish individuals who are at risk, limiting preventive measures.

Material and methods We investigated the skeletal system of sportswomen who did sustain SF in the past (n = 19) and compared it with that of female controls (C) with a similar sporting history but without any fracture history (n = 20).

Bone mass and body composition were measured using dual-energy X-ray absorptiometry. Bone micro-architecture was investigated by calcaneal ultrasound and fractal analysis of calcaneus radiographic images. Oestradiol levels were measured by E.I.A, and IGF-1 by R.I.A. Menstrual characteristics, nutrient intake, and training were assessed using questionnaires.

Results The result of the fractal analysis, expressed by the Hmean parameter, was significantly lower in the SF group, reflecting a more complex structure of the trabecular micro-architectural organization (P < 0·005). Body mass index (BMI) at birth was also found to be lower in the SF cases as compared with their C (P < 0·03).

Multivariate analysis revealed that the fractal parameter Hmean, bone mineral content (BMC) at Ward's triangle and the BMI at birth correctly assigned 84·85% of the female athletes into their respective SF or C groups (P = 0·001).

Conclusion These results suggest that the fractal parameter and the BMI at birth may be able to identify female athletes most at risk for this overuse bone injury, as their low indexes might reflect a greater skeletal sensitivity.

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Much has been written about the anti-immigrant movement of the 1990s and beyond. Since the events of 9/11 this movement has been transformed to include a srtong anti-Islam aspect. Little has been written about the gendered aspects of these movements. There are three main issues to be discussed in this paper: First the greater strength of the movement amongst men, as compared with women. Second, the predominantly male leadership, albeit with important exceptions. Third, since 9/11 the imagery has been transformed from a simple nativist one, to a gendered frame where the immigrant is portrayed as a threat to the gendered sexual order. 9/11 has allowed anti-immigrant attitudes to become acceptable as immigrantion by non-westerners is depicted as a threat to the western way of life.

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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.

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Since contours often contain many different sized structures they need to be described at multiple scales. Rather than describe a contour at all scales it is more efficient to identify the most significant scales that best represent the structures present. These natural scales are determined by examining the Fourier descriptors of the contour and searching for significant bands. These correspond to bandwidths required to extract features at qualitatively significant resolution. Examples are given of using the determined scales in both low pass and high pass filters to eliminate fine and coarse detail.

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The problem of object recognition is of immense practical importance and potential, and the last decade has witnessed a number of breakthroughs in the state of the art. Most of the past object recognition work focuses on textured objects and local appearance descriptors extracted around salient points in an image. These methods fail in the matching of smooth, untextured objects for which salient point detection does not produce robust results. The recently proposed bag of boundaries (BoB) method is the first to directly address this problem. Since the texture of smooth objects is largely uninformative, BoB focuses on describing and matching objects based on their post-segmentation boundaries. Herein we address three major weaknesses of this work. The first of these is the uniform treatment of all boundary segments. Instead, we describe a method for detecting the locations and scales of salient boundary segments. Secondly, while the BoB method uses an image based elementary descriptor (HoGs + occupancy matrix), we propose a more compact descriptor based on the local profile of boundary normals’ directions. Lastly, we conduct a far more systematic evaluation, both of the bag of boundaries method and the method proposed here. Using a large public database, we demonstrate that our method exhibits greater robustness while at the same time achieving a major computational saving – object representation is extracted from an image in only 6% of the time needed to extract a bag of boundaries, and the storage requirement is similarly reduced to less than 8%.

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Here, we for the first time synthesized bimetallic Cu/Ag dendrites on graphene paper (Cu/Ag@G) using a facile electrodeposition method to achieve efficient SERS enhancement. Cu/Ag@G combined the electromagnetic enhancement of Cu/Ag dendrites and the chemical enhancement of graphene. SERS was ascribed to the rough metal surface, the synergistic effect of copper and silver nanostructures and the charge transfer between graphene and the molecules.