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| Trademark recognition has been played a very important part in our daily life, which can be applied to various fields such as advertisement, logistics transportation network, E-commerce and so on. In this paper, a fast trademark recognition method based on shape context is proposed to detect and classify the trademarks in images. However, the difficulties lie in that when the sample set becomes larger, along with the calculation of the feature points matching increases, the computational efficiency greatly reduced. The method proposed in this paper attempts to cluster the feature vectors in training procedure so that the search scope of K nearest neighbors in KNN algorithm could be narrowed. The experimental results show that the modified algorithm has faster computing speed on the basis of maintaining the previous performance, and do well in trademark recognition. |
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| Keywords:trademark recognition; shape context; object matching; clustering |
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