Abstract
This paper deals with the techniques for improving image classification by extracting geometric attributes of objects. In this paper, we first introduce one kind of symmetry transform called directional symmetry transform, which can provide more geometric information about objects. Based on it, we present one algorithm for improving image classification by determining scale factors relating to supervised learning. The results show that the number of the mixed pixels can be efficiently reduced by using the proposed method.
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