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A document skew detection method using the Hough Transform
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AI
DOI：10.1007/s100440070009.png)
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摘要
En 中文
Document image processing has become an increasingly important technology in the automation of office documentation tasks. Automatic document scanners such as text readers and OCR (Optical Character Recognition) systems are an essential component of systems capable of those tasks. One of the problems in this held is that the document to br read is not always placed correctly on a flat-bed scanner. This means that the document may be skewed on the scanner bed, resulting in a skewed image. This skew has a detrimental effect on document analysis, document understanding, and character segmentation and recognition, Consequently, detecting the skew of a document image and correcting it are important issues in realising a practical document reader. in this: paper we describe a new algorithm for skew detection. We then compare the performance and results of this skew detection algorithm to other published methods from O'Gorman, Hinds, Le, Baird, Postl and Akiyama. Finally, we discuss the theory of skew detection and the different approaches taken cu solve the problem of skew in documents. The skew correction algorithm we purpose has been shown tu br extremely fast, with run times averaging under 0.25 CPU seconds to calculate the angle on a DEC 5000/20 workstation.
Keyword:
connected components
document analysis
Hough transform
least square method
projection profile
skew detection
