Image Segmentation as a Classification task
نویسندگان
چکیده
We implement two-class classification model for image segmentation. This project draws loosely on [1]. In a preprocessing stage an image is oversegmented into superpixels by normalized cut algorithm. For a segment as a mergence of superpixels, we define two features based on similarity in brightness. We train a logistic regression classifier to combine these features. As a ground truth segmentation, we use the database of segmentation produced by human. Finally we conduct experiments and qualitatively evaluate the results.
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