Pattern and Character Recognition

Three researchers at Concordia University, in Canada, published a paper that Shane found, describing a very accurate method of character recognition. When run on a set of chinese characters, it had a high accuracy rate even under various rotations and significant noise.

Chen, Bui, and Krzyzak (the authors) reported 98.8% accuracy or higher on the chinese characters present in Figure 1. Since our set of possible characters is approximately a third of theirs, their method would be extremely useful for us. Additionally, their 98.8% accuracy was obtained with high white noise (see Figure 2, SNR = 0.5). With a SNR of 1.0 or higher, their accuracy was 100% under all rotational angles.

Their approach involves the Radon transform, dual-tree Complex Wavelet, and Fourier transforms. Both the Radon transform and the Fourier transform benefit highly from the GPU programming we will be using, and likely the dual-tree Complex Wavelet will as well.

I also found another student who had experience implementing a Radon transform in C++, though he did not use the GPU.

Figure 1:

Figure 2: