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Image segmentation framework based on multiple feature spaces
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DOI：10.1049/iet-ipr.2014.0236.png)
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Abstract
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Image segmentation plays a key role in many fields such as image processing and recognition. Although various segmentation methods have been proposed in recent decades, most of these methods are based on only a single feature space. How to combine various features to image segmentation is a challenge problem. To address this problem, the authors propose to combine different features based on evolutionary multiobjective optimisation. Two optimisation objectives, which are based on colour and texture features, respectively, are therefore designed for image segmentation. The experiments show that the author's method is able to combine multiple features for image segmentation successfully.
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