Character separation method of tightly-connected character strings in complex environment

Abstract

The invention discloses a character separation method of tightly-connected character strings in complex environment and belongs to the technical field of image processing. Envelope information of the character strings is utilized to primarily position a primary partition point, a secondary partition point is generated according to filtering processing of the primary partition point, a primary segmentation point is obtained, calibration is carried out on the primary segmentation point in the end to accurately position a segmentation position, and therefore cutting processing of collected word string images can be achieved, and the purpose of separating the tightly-connected character strings in the complex environment is achieved. The character separation method of the tightly-connected character strings in the complex environment achieves segmentation of the tightly-connected character strings in the complex environment, and is applied to different character styles, low in algorithm complexity, and high in segmentation accuracy.

Description

Technical field [0001] The invention relates to a character separation method for closely connected character strings, and is particularly suitable for a method for segmenting digital strings in various real bills. Background technique [0002] Bills are a tool often used in daily life and work. In order to more conveniently convert some information on bills into digital information for subsequent processing, some automatic identification processing methods are usually used. A very important step before recognizing characters is to separate the character string to be recognized. However, the complicated background information and closely-connected characters in the bill are the difficulties faced by various current segmentation methods. Therefore, the segmentation of tightly connected strings in complex environments has great research value and application prospects. [0003] There are three segmentation methods commonly used at present. The first is the horizontal projection met...

AI Technical Summary

Problems solved by technology

[0003] There are three commonly used segmentation methods at present. The first is the horizontal projection method, that is, according to the horizontal direction, calculate the lowest point of the projection in the vertical direction, and obtain the segmentation position belonging to the target character. , the feasibility of this method will be greatly reduced, background noise and adhesion will affect the accuracy of projection segmentation, and thus wrongly calculate the location of the segmentation

Another method that is often used at present is to segment characters through the connectivity of characters, that is, to segment according to the principle that pixels belonging to the same character form a connected area. This method is clear and connected to character points such as license plate recognition. It is very practical when the area is obvious, but it is not applicable to the situation where characters are often glued in real bills, and the accuracy rate is very low

The third is the cutting algorithm based on template matching. According to the structure and size characteristics of the string, a string template is designed, and such a template is used to slide and match the license plate area to cut the characters to determine the best matching position. However, this method, There will be a big problem with various fonts in various bills, because it only applies to one font, or different fonts with little change

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