Separating Chinese Character from Noisy Background Using GAN

Figure 2

The network structure of the DESRGAN. An image with overlapping handwritten and printed characters is first processed by a series of convolution and RRDB modules. There is an operation of dilated convolution inside each residual-in-residual dense block. The generator outputs separated printed part or handwritten part from the overlapping. The discriminator classifies separated printed or handwritten characters and ground truth into real or fake.