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Learning the Optimal Transformation of Salient Features for Image Classification

Zhou, Jun; Fu, Zhouyu; Robles-Kelly, Antonio


In this paper, we address the problem of recovering an optimal salient image descriptor transformation for image classification. Our method involves two steps. Firstly, a binary salient map is generated to specify the regions of interest for subsequent image feature extraction. To this end, an optimal cut-off value is recovered by maximising Fisher's linear discriminant separability measure so as to separate the salient regions from the background of the scene. Next, image descriptors are...[Show more]

CollectionsANU Research Publications
Date published: 2009
Type: Conference paper
Source: Proceedings of the Digital Image Computing: Techniques and Applications (DICTA 2009)
DOI: 10.1109/DICTA.2009.28


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