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.Taking characteristic extraction of interesting ground object from RS（Remote Sensing） images as the example，image classification process based on distribution computation is implemented.Experimental results based on .Net environment show that new model improves classification speed and efficiency of data-intensive images.

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。