Visual words sequence alignment for image classification

Abstract

In recent years, the field of image processing has been gaining a growing interest in many scientific domains. In this paper, the attention is focused on one of the fundamental image processing problems, that is image classification. In particular, the novel approach of bridging content based image retrieval and sequence alignment domains was introduced. For this purpose, the dense version of the SIFT key point descriptor, k-means for visual dictionary construction and the Needleman-Wunsch method for sequence alignment were implemented. The performed experiments, which evaluated the classification accuracy, showed the great potential of the proposed solution indicating new directions for development of new image classification algorithms.