Description: Deskew is the preprocessing operation of removing skew from images (especially bitmaps created using a scanner).
Skew is an artifact that can occur in scanned images because of the camera being misaligned, imperfections in the scanning or surface, or simply because the paper was not placed completely flat when scanned.
DeskewHelper allows automatic skew detection and correction.
Skew detection and correction is a very important problem when an OCR algorithm tries to detect and interpret characters from the source document. Many different solutions have been developed. The stage in which the skew detection takes place also varies from the first to the very last one before the OCR phase.
The document structure analysis and character recognition are usually done in several phases: scanning and thresholding, image enhancement, skew detection and correction, segmentation, classification and character recognition. Each step must be completed well enough for the performance of the sequence and result to be successful. Steps that follow the skew correction are inefficient if the correction fails.
The steps used to deskew an image are:
Calculate the slope of the document
Compute the rotation angle
Calculate the size of a new image large enough to hold the rotated image
Allocate the new image
Rotate the entire image
Please test the speed and accuracy of DeskewHelper by downloading the demo application! DeskewHelper expects as input a monochrome image.
LandscapeHelper 1.0 LandscapeHelper detects landscape pages (rotated with 90 degrees) and automatically put the image into the right position for further processing steps (character recognition). The
ZoneHelper 1.0 ZoneHelper detects and automatically converts inverted text zones and change white-on-black text to normal black-on-white text. Typical OCR software can handle only binary images
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