With the improvement of the spatial resolution of remote sensing image

the objective basis is provided for extracting the texture and shape features

at the same time

the traditional pixel-based classification methods are challenged severely.So it is necessary to improve existing methods or to develop new one.In this paper

according to object-oriented analysis method

firstly a serial of pre-processing procedures are performed

such as image segmentation

edge tracing and vectorization

and vectorization compression;then the shape features are extracted from the vectorization information

finally with the help of the spectral feature and shape features

the classification for two kinds of typical artificial objects is finished by using the fuzzy classifier

and the classification accuracy is evaluated by visual interpretation.The results show that the extraction of shape features enriches enormously the feature database for object identification

especially under the condition when the object of interest and background have the similar spectral reflection and the apparent different shape features

this object-oriented classification by integrating spectral and shape features can improve greatly the identification accuracy.