Web-based image classification systems aim to provide users with an easy access to image classification function. The existing work mainly focuses on web-based unsupervised classification systems. This paper proposes a web-based supervised classification system framework which includes three modules: client, servlet and service. It comprehensively describes how to combine the procedures of supervised classification into the development of a web system. A series of methods are presented to realize the modules respectively. A prototype system of the framework is also implemented and a number of remote sensing (RS) images are tested on it. Experiment results show that the prototype is capable of accomplishing supervised classification of RS images on the Web. If appropriate algorithms and parameter values are used, the results of the web-based solution could be as accurate as the results of traditional desktop-based systems. This paper lays the foundation on both theoretical and practical aspects for the future development of operational web-based supervised classification systems.
Sun, Z., H. Fang, L. Di, P. Yue, X. Tan, and Y. Bai, 2016: Developing a web-based system for supervised classification of remote sensing images. Geoinformatica, 20, 629–649, doi:10.1007/s10707-016-0252-3This material is based upon work supported by the National Science Foundation under Grant No. 1440294. Opinions, findings, conclusions or recommendations expressed are those of the authors and do not reflect the views of the NSF.