Image classification based on saliency coding with category-specific codebooks

This paper presents a feature encoding scheme for image classification by combining the salient coding method with the category-specific codebooks, which are generated separately using the training images of each category. Different from the usual way of concatenating or merging the category codebooks to form a global dictionary, we employ the category codebooks to calculate a type of category-sensitive saliency feature, and then, encode the saliency features to form a representation of image content. Compared to the state-of-the-art methods such as LC-KSVD, the dictionary generation and feature encoding in our scheme are pretty simple, and no complicated optimization is involved. However, our scheme can achieve better, in some cases, significantly better results, in terms of the classification accuracy, than the state-of-the-art methods. Extensive experiments are carried out to show the effectiveness of our method in comparing with various image classification methods.