关键词: 图像分类机制, 特征库, 实时性, 分类节点, 特征匹配

Abstract: Aiming at the problem of long timeconsuming and poor realtime of large data images classification, using the advantages of cloud computing technology to obtain the ideal classification results of large data images, we proposed a large data image classification mechanism based on Hadoop platform. Firstly, a large number of images were collected, the image database was constructed, and the effective features of the image classification were extracted. Secondly, based on the Hadoop platform, the Map function was used to subdivide the large data image classification problems, and subproblems were classified and solved by multiple nodes parallel and distributed, and the corresponding image classification results were obtained. Finally, the Reduce function was used to combine image classification results of subproblems, and the simulation test of large data image classification was realized  by using VC++60 programming. Test results show that the proposed classification mechanism can overcome the drawbacks of current image classification mechanism,  greatly shorten  the time of image classification, and the classification speed can adapt to online requirements of large data image classification, and the overall effect of image classification is obviously superior to the other image classification mechanisms.

Key words: image classification mechanism, feature database, realtime, classification node, feature matching