Recognition of low-resolution characters by a generative learning method
نویسندگان
چکیده
Using appropriate training data is necessary to robustly recognize low-resolution characters by the subspace method. Former learning methods used characters actually captured by a camera, which required the collection of characters of all categories in various conditions. In this paper, we propose a new learning method that generates training data by a point spread function estimated beforehand by captured images. This method is efficient, since it eliminates collection of the training data. We confirmed its usefulness by experiments.
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