【摘要】 为了充分利用网格技术分布式、高性能、协同共享的能力,设计了一种基于网格和支持向量机的分布式图像分类器模型,采用网格计算技术,统筹网络运算资源,结合支持向量机在有限样本统计分类中的优势,探索网格技术在图像分类中的应用。以对遥感图像目标物体的特征提取为例,实现基于分布式计算的图像分类过程,基于.net环境的实验结果表明,该模型提高了数据密集型图像分类速度和处理效率。更多还原

【Abstract】 Distributed image classification model based on grid and support vector machine is put forward in this paper to make full use of grid characteristic,such as distribution,high-performance and collaborative sharing capabilities etc.New model utilizes grid computing technology,plans as a whole of network computing resources,combines with statistic classification advantage of support vector machine in finite sample space,probes into application of grid computation technology in image classification.Tak- ing characteristic extraction of interesting ground object from RS(Remote Sensing) images as the example,image classification pro- cess based on distribution computation is implemented.Experimental results based on .Net environment show that new model im- proves classification speed and efficiency of data-intensive images.更多还原