Method and equipment for character identification post-processing and image picking equipment comprising equipment

Abstract

The invention relates to a method and equipment for character identification post-processing and image picking equipment comprising the equipment. The method comprises steps that assembly identification, an assembly is extracted from a character row area image, and an assembly identification result is acquired; acquisition of a top point and a bottom point, the top point and the bottom point of the assembly having the largest distance from a character direction line are acquired; determination of disappearance points, the disappearance points are determined by utilizing a cross point of a top line and a bottom line, the top line is determined by top point sets of line segments with gradients and intercepts in mutual consistency on the basis of line segments of any two top points of each assembly, and the bottom line is similar to the top line and is determined by bottom point sets of line segments with gradients and intercepts in mutual consistency on the basis of line segments of any two bottom points of each assembly; determination of base lines, at least two base lines are determined on the basis of the determined disappearance points; and character correction, the identification result is corrected on the basis of the determined base lines.

Description

technical field [0001] The present application generally relates to the fields of computer vision and image processing, and in particular to a character recognition post-processing method and a character recognition post-processing device that can provide accurate baseline calculation results under severe perspective distortion. The present application also relates to an image pickup device including the character recognition post-processing device. Background technique [0002] With the development of handheld devices equipped with cameras, there is an urgent need for camera-based mobile OCR (Optical Character Recognition) applications in a variety of environments, such as outdoor digitization of documents, recognition of street signs in foreign languages, and OCR for the visually impaired. Phonetic input, etc. [0003] A traditional character recognition process generally includes a text area detection step, a preprocessing step, a character cutting step, a character reco...

AI Technical Summary

Problems solved by technology

This method does not filter out unreliable points (or lines) and is therefore imprecise

Furthermore, it is difficult to obtain reliable vanishing points by this method when the number of endpoints is small

[0011] It can be seen that the methods in the prior art have the problem that it is difficult to accurately and effectively calculate the baseline for post-processing in the case of severe perspective distortion or short text

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