Image retrieval based on multiple visual features is one of most important direction in the field of content-based image retrieval. Existing retrieval algorithms are based on multiple features mainly combining features through linear weighting. However

this just achieves combinations in the sense of algebra

and the retrieval result is susceptible to the choice of the weights. To solve this problem

including the extraction of shape and color information in the feature extraction procedure

we propose a method to construct combined shape-color features

called shape-color moment invariants

which are invariant to both shape affine transformation and color diagonal-offset transformations. First

we define the shape core and color core in the two-dimensionol geometric space and three-dimensionol color space respectively. Then multiple integrals to the product of shape core and color core are produced. Finally

we get an invariant feature by normalization. Theoretically

this method can derive an infinite number of invariant features while choosing different shape cores or color cores. The experimental results show that this method is distinctive to existing linear weighting method

and has better performance and efficiency when retrieving near-duplicated images

images with similar property

broadly similar images etc.