Abstract
A new signal processing method is developed for estimating the skew angle in text document images. Detection of the skew angle is an important step in text processing tasks such as optical character recognition (OCR) and computerized filing. Based on a recently introduced multiline-fitting algorithm, the proposed method reformulates the skew detection problem into a special parameter-estimation framework such that a signal structure similar to the one in the field of sensor array processing is obtained. In this framework, straight lines in an image are modeled as wavefronts of propagating planar waves. Certain measurements are defined in this virtual propagation environment such that the large amount of coherency that exists between the locations of the pixels on parallel lines is exploited to enhance a subspace in the space spanned by the measurements. The well-studied techniques of sensor array processing (e.g., the ESPRIT algorithm) are then exploited to produce a closed form and high-resolution estimate for the skew angle.
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Aghajan, H.K., Khalaj, B.H. & Kailath, T. Estimation of skew angle in text-image analysis bySLIDE: Subspace-based line detection. Machine Vis. Apps. 7, 267–276 (1994). https://doi.org/10.1007/BF01213417
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DOI: https://doi.org/10.1007/BF01213417