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Motion blur characterization and compensation for line scan (1D) cameras

Line sensors (1D) are often used for quality monitoring of moving objects in industrial environments. They are, for instance, used to derive dimensional and geometrical information of moving objects or products. Their high sampling rate makes them well suited for retrieving information of fast moving objects. However, in fast motion the 1D sensor, as any other kind of image sensor, introduces artefacts commonly referred to as motion blur. In this paper, we discuss (1D) sensor motion blur and methods to compensate for it. An experimental set-up and a simulation tool have been developed to characterize motion blur of (1D) sensors. Once properly characterized, a deblurring algorithm (based on a non-blind deconvolution method) has been developed to reconstruct a deblurred image. The results are validated using experimental data collected from a vibrating string. Comparison between dimensional feature measurements of the vibrating string, without and with deblurring methods are illustrated. The analysis shows that a decrease by a factor of two on the measurement variance can be achieved by applying the proposed deblurring method.