An integrated aurora image retrieval system: AuroraEye

With the digital all-sky imager (ASI) emergence in aurora research, millions of images are captured annually. However, only a fraction of which can be actually used. To address the problem incurred by low efficient manual processing, an integrated image analysis and retrieval system is developed. For precisely representing aurora image, macroscopic and microscopic features are combined to describe aurora texture. To reduce the feature dimensionality of the huge dataset, a modified local binary pattern (LBP) called ALBP is proposed to depict the microscopic texture, and scale-invariant Gabor and orientation-invariant Gabor are employed to extract the macroscopic texture. A physical property of aurora is inducted as region features to bridge the gap between the low-level visual features and high-level semantic description. The experiments results demonstrate that the ALBP method achieves high classification rate and low computational complexity. The retrieval simulation results show that the developed retrieval system is efficient for huge dataset. (c) 2010 Elsevier Inc. All rights reserved.

Effect of Crystallographic Texture on Magnetic Characteristics of Cobalt Nanowires

Cobalt nanowires with controlled diameters have been synthesized using electrochemical deposition in etched ion-track polycarbonate membranes. Structural characterization of these nanowires with diameter 70, 90, 120 nm and length 30 mu m was performed by scanning electron microscopy, high-resolution transmission electron microscopy, and X-ray diffraction techniques. The as-prepared wires show uniform diameter along the whole length and X-ray diffraction analysis reveals that [002] texture of these wires become more pronounced as diameter is reduced. Magnetic characterization of the nanowires shows a clear difference of squareness and coercivity between parallel and perpendicular orientations of the wires with respect to the applied field direction. In case of parallel applied field, the coercivity has been found to be decreasing with increasing diameter of the wires while in perpendicular case; the coercivity observes lower values for larger diameter. The results are explained by taking into account the magnetocrystalline and shape anisotropies with respect to the applied field and domain transformation mechanism when single domain limit is surpassed.

On Combining Morphological Component Analysis and Concentric Morphology Model for Mammographic Mass Detection

Mammographic mass detection is an important task for the early diagnosis of breast cancer. However, it is difficult to distinguish masses from normal regions because of their abundant morphological characteristics and ambiguous margins. To improve the mass detection performance, it is essential to effectively preprocess mammogram to preserve both the intensity distribution and morphological characteristics of regions. In this paper, morphological component analysis is first introduced to decompose a mammogram into a piecewise-smooth component and a texture component. The former is utilized in our detection scheme as it effectively suppresses both structural noises and effects of blood vessels. Then, we propose two novel concentric layer criteria to detect different types of suspicious regions in a mammogram. The combination is evaluated based on the Digital Database for Screening Mammography, where 100 malignant cases and 50 benign cases are utilized. The sensitivity of the proposed scheme is 99% in malignant, 88% in benign, and 95.3% in all types of cases. The results show that the proposed detection scheme achieves satisfactory detection performance and preferable compromises between sensitivity and false positive rates.