Abstract—This work aims to enhance the matching and retrieval performance over image datasets which have similar spatial structures that occur very frequently. Instead of treating images as bags of features, we try to encode the spatial relationships in the representation. This process would help to resolve the ambiguity when two classes of images have similar sets of features although in different spatial arrangements. To demonstrate the fact a sizeable dataset of license plate images is used. We have proposed a method to use graphs to encode the spatial relationships among features. The problem of image matching thus turns to finding the maximum similarity between labelled graphs. It is shown that the precision of the retrieved results increases with this matching scheme since most of the false matches are eliminated. I
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