4 resultados para image classification
em Chinese Academy of Sciences Institutional Repositories Grid Portal
Resumo:
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.
Resumo:
对薄板成形应变场传统的测量方法进行了研究,指出了其不足和误差的来源,提出了数字图像分析法测量薄板成形中的应变场,对测量原理、新的测量方法对传统方法的改进,以及如何降低误差进行了介绍,指出数字图像分析法的前景,提出了改进意见。
Resumo:
A new particle image technique was developed to analyze the dispersion of tracer particles in an internally circulating fluidized bed (ICFB). The movement course and the concentration distribution of tracer particles in the bed were imaged and the degree of inhomogeneity of tracer particles was analyzed. The lateral and axial dispersion coefficients of particles were calculated for various zones in ICFB. Results indicate that the lateral diffusion coefficient in the fluidized bed with uneven air distribution is significantly higher than that in uniform bubbling beds with even air distribution. The dispersion coefficients are different along bed length and height.