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A New Anchor-Labeling Method For Oriented Text Detection Using Dense Detection Framework
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DOI：10.1109/LSP.2018.2852954.png)
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This letter proposes a new method for dense scene text detection anchor box labeling using single-shot multibox detection (SSD) as the base framework and VGG16 as the backbone, enhanced for scene text detection. This method can be further generalized to other detection tasks with various aspect ratios. We argue that the loU criterion used by the dense object detection framework may have low recall ratios in extreme aspect ratio cases and oriented objects, and we propose a new criterion of the anchor-labeling method for these kinds of objects. The result shows that this method has better performance on public datasets compared with the previous labeling methods.
Keyword:
Deep neural network (DNN)
geometry transformation
text detection
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9.6
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1.1W
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1.7W
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