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Binary method for low-quality document image based on local contract and estimation of stroke width

A local contrast and stroke width technology, applied in the field of image processing, can solve the problem of missing character strokes and other problems, achieve good robustness, suppress ink infiltration, and retain the effect of character stroke details

Inactive Publication Date: 2016-03-02
HUBEI UNIV OF TECH
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Problems solved by technology

The Otsu algorithm has a good segmentation effect for images with a large difference between the foreground and the background, that is, images with significant bimodal features in the histogram, but when processing low-quality document images, some or even all character stroke details will be lost

Method used

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  • Binary method for low-quality document image based on local contract and estimation of stroke width
  • Binary method for low-quality document image based on local contract and estimation of stroke width
  • Binary method for low-quality document image based on local contract and estimation of stroke width

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Embodiment Construction

[0047] Process of the present invention picture See figure 1 , the steps are to obtain a scanned document image, grayscale the color image, detect local image contrast, Otsu global optimal thresholding, character stroke width estimation, and local image binarization. details as follows:

[0048] 1) Obtain the scanned document image;

[0049] 2) Gray-scale color image; the minimum mean value method is used to gray-scale the color image, and the gray-scale image obtained has color independence.

[0050]At present, methods such as component weighted average, average value, and maximum value are mainly used to grayscale color images.

[0051] Weighted average method: u gray (x,y)=0.2989×u R (x,y)+0.5870×u G (x,y)+0.1140×u B (x,y)

[0052] Average method: u g r a y ( x , y ) = ...

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Abstract

The invention relates to a binary method for a low-quality document image based on local contract and estimation of stroke width. The method comprises the steps that the scanned document image is obtained; the colored document image u (x, y) is grayed in a minimum mean method; character stroke pixel is detected based on the local contrast; global optimal thresholding is carried out on the obtained local contract image in an Otsu method; edge detection is carried out on the binary image via a Canny operator, the amount nfg of the character foreground pixels and the amount nedge of the character edge pixels are calculated respectively, the contour proportion lambda is calculated by dividing the nfg by the nedge, and the character stroke width is estimated via the contour proportion; and image local binarization is carried out in a sliding neighborhood method. According to the method, details of character strokes are reserved effectively, the character foreground is effectively segmented, and phenomena including ink marks infiltration, spot of pages, textured background, and non-uniform illumination can be inhibited.

Description

technical field [0001] The invention relates to a low-quality document image binarization method based on local contrast and stroke width estimation, and belongs to the technical field of image processing. Background technique [0002] Document Analysis and Recognition (DAR) technology has been widely used in printed characters and formula recognition, handwritten character recognition, document image segmentation, video subtitle extraction, text information retrieval and other fields, mainly including image acquisition, preprocessing, binarization, layout Analysis, OCR identification, indexing and other processes. Image binarization is one of the key processing steps, which directly affects the performance of the DAR system. However, binarization of such low-quality document images is extremely challenging due to factors such as image contrast, ink smearing, page stains, or uneven lighting. [0003] At present, many document image binarization algorithms have been propose...

Claims

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Application Information

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IPC IPC(8): G06T5/00
Inventor 熊炜李敏周少文赵楠武明虎徐晶晶赵诗云
Owner HUBEI UNIV OF TECH
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