EFFICIENT MOTION DEBLURRING FOR INFORMATION RECOGNITION ON MOBILE DEVICES

In this paper, a new method for the identification and removal of image artifacts caused by linear motion blur is presented. By transforming the image into the frequency domain and computing its logarithmic power spectrum, the algorithm identifies the parameters describing the camera motion that caused the blur. The spectrum is analysed using an adjusted version of the Radon transform and a straightforward method for detecting local minima. Out of the computed parameters, a blur kernel is formed, which is used to deconvolute the image. As a result, the algorithm is able to make previously unrecognisable features clearly legible again. The method is designed to work in resource-constrained environments, such as on mobile devices, where it can serve as a preprocessing stage for information recognition software that uses the camera as an additional input device.