Image Classification Based on Sparse Representation and ROI

Abstract:

A new image classification method based on regions of interest (ROI) and sparse representation is introduced in the paper. Firstly, the saliency map of each image is extracted by different methods. Then, we choose sparse representation to represent and classify the saliency maps. Four different ROI extraction methods are chosen as examples to evaluate the performance of the proposed method. Experimental results show that it is more effective for image classification based on ROI.

• Periodical: Applied Mechanics and Materials (Volumes 556-562)
• Pages: 4906-4910
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.556-562.4906
• Online since: May 2014
• Authors: Hui Hui Zhao*, Jun Ding Sun
• Keywords: Image Classification, Regions of Interest, Sparse Representation

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