417 bar code identification method based on sub-pixel edge detection

Abstract

The invention discloses a 417 bar code identification method based on sub-pixel edge detection, which aims at defects of the traditional 417 bar code identification method such as slow processing, poor anti-interference performance, large error an the like. The 417 bar code identification method based on sub-pixel edge detection can identify 417 bar codes fast, accurately and efficiently, and is very remarkable in identification effect especially when image resolution ratio of the 417 bar codes is low. When the 417 bar codes are blurring in images or poor in printed quality, the 417 bar code identification method also has a certain effect on improvement of 417 bar code recognition rate. The 417 bar code identification method is further suitable for conditions of intercepted 417 bar codes. The 417 bar code identification method based on sub-pixel edge detection has good instantaneity, strong fouling resistance and high identification efficiency, and can be widely applied to smart phones and other terminal embedded devices.

Description

technical field [0001] The invention relates to a barcode automatic recognition method, especially an efficient 417 barcode recognition method based on sub-pixel edge detection, which can quickly, accurately and efficiently recognize 417 barcodes, especially in the 417 barcode image resolution When the rate is low, the recognition effect of this method is very significant. When the image of the 417 barcode is blurred or the printing quality is poor, this method also has a certain effect on improving the recognition rate of the 417 barcode. Background technique [0002] Automatic data collection technology is the key technology of information collection and processing, and barcode recognition technology plays an important role in automatic data collection. Two-dimensional barcodes are developed on the basis of traditional one-dimensional barcodes. Due to the limitation of information capacity, the traditional one-dimensional barcode must rely on the support of the database;...

AI Technical Summary

Problems solved by technology

[0004] The disadvantages of the traditional processing method are: 1. Rotate the 417 barcode to the horizontal direction

If the method based on straight line fitting is used, the straight line obtained under the condition of noise interference is not necessarily the boundary of the 417 barcode, and the rotation based on this will inevitably have a large error

If the method based on Hough transform is adopted, it will take more time;

[0005] 2. Using the idea of ​​edge detection and projection to calculate function information parameters, 2.1 On the one hand, edge detection is sensitive to noise and has poor anti-noise ability

If filtering is used, the filtering operation optimization takes a certain amount of time

2.2 The projection calculation based on the horizontal and vertical directions takes time. On the other hand, after obtaining the peak value, the method of controlling the error limit is used to calculate the functional information parameters, and the error is large;

[0006] 3. The symbol characters are very important for the correct recognition of the 417 barcode. The traditional method is to use the traditional edge detection algorithm to perform edge detection and then project in the vertical direction or use the minimum module width to extract the symbol characters. Segment the module corresponding to the 417 barcode symbol characters, especially when the 417 barcode image has low resolution, stains, and poor printing quality, the success rate of extracting symbol characters is very low, resulting in the 417 barcode not being correct Identified

In short, the traditional 417 barcode processing method is slow in processing speed, time-consuming, large in error, low in recognition rate, and low in efficiency. It is difficult to achieve real-time performance and wide application and popularization in various industries.

Images