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Code128 bar code automatic reading method based on global optimization

A global optimization, barcode technology, applied in the field of barcode recognition, can solve problems such as reducing work efficiency, affecting overall code recognition, and high rejection rate

Pending Publication Date: 2020-07-03
CHENGDU UNIV OF INFORMATION TECH
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0008] As we all know, barcodes are used in a wide range of scenarios, including some harsh environments. Therefore, many factors such as printing quality problems, contamination during transportation, barcode area deformation or reflection, etc., will affect the recognition of any of the above traditional image processing solutions. The reading will cause irreversible impact, and finally affect the recognition of the overall code, resulting in a high rejection rate, which has to be read again or manually input, which greatly reduces the work efficiency

Method used

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  • Code128 bar code automatic reading method based on global optimization
  • Code128 bar code automatic reading method based on global optimization
  • Code128 bar code automatic reading method based on global optimization

Examples

Experimental program
Comparison scheme
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Embodiment 1

[0051] A Code128 barcode automatic reading method based on global optimization, such as figure 1 , mainly including the following steps in sequence:

[0052] Step (1) calculates four probability values ​​{p that may be 1 to 4 for each character 1 ,p 2 ,p 3 ,p 4};

[0053] Step (2) uses the formula w i = log p i the probability value p i Transformed into the expression of information entropy, the four probability values ​​of each character calculated in step (1) are calculated to obtain the product calculation equivalent of the maximum probability into the sum calculation of obtaining the maximum information entropy:

[0054] Step (3) adopts the mode of global probability optimization to obtain the character that its maximum probability may correspond to;

[0055] Step (4) According to the values ​​of all data bits in step (3) under the condition of maximum total probability, corresponding to the Code128 coding table, the corresponding barcode coding information is d...

Embodiment 2

[0063] The only difference between this embodiment and Embodiment 1 is that since the character composition corresponding to each character is completely fixed and the number is extremely limited, the present invention uses the following steps to complete the global probability optimization to obtain the character that may correspond to the maximum probability, mainly Include the following steps in order:

[0064] Step (3-1) Manually design a 24×107 sparse weight matrix G according to the Code128 coding table, where each column corresponds to a character, and the 24 data elements in each column are equally divided into 6 units, corresponding to 6 characters, Each unit contains 4 data elements corresponding to the four possible values ​​of the character; when the i-th character takes the value j according to the coding rules, the corresponding data element of the corresponding character in the 4i+j column The value is 1, otherwise it is 0, so for each column of the weight matri...

Embodiment 3

[0075] The difference between this embodiment and embodiment 2 is that further, step (3-1) to step (3-3) and step (3-4) to step (3-8) in said step (3) , can also be replaced by HMMs, MRFs, bipartite graphs, graph cuts or TVL1 optimization methods to obtain the corresponding value of the maximum probability that each character includes a check digit.

[0076] Here, other HMMs and MRFs optimization algorithms can be used to replace the two optimization steps in the above step 3, which should still be protected by the claims of the present invention. More specifically, the above step (3) uses an HMMs optimization method that is more efficient for this problem, but other optimization algorithms include but are not limited to algorithms such as bipartite graphs, graph cuts, and TVL1. Replacement, but because it is only a non-inventive modification or simple replacement made to step (3) of the present invention, these optimization methods are still protected by the present invention...

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Abstract

The invention discloses an automatic Code128 bar code reading method based on global optimization, and relates to the field of barcode recognition, the method includes converting the probability valueinto an information entropy expression mode; therefore, the product calculation for solving the maximum probability is equivalently transformed into the summation calculation for solving the maximuminformation entropy; the method comprises the following steps of: obtaining probability values, namely information entropies, of six characters in a certain character; obtaining a character possibly corresponding to the maximum probability by adopting a global probability optimization mode; a character recognition result does not only depend on accurate recognition of each single character; secondly, correcting a result among all the characters by utilizing a code128 check rule; according to the technical scheme, the maximum total probability of the recognition result is taken as the target onthe premise that the recognition result meets the coding rule, the final decoding result does not depend on accurate recognition of each character, and the problems that bar code image imaging is damaged due to multiple factors of a bar code, and an existing bar code processing scheme has a high bar code rejection rate are solved.

Description

technical field [0001] The invention relates to the field of barcode identification, in particular to an automatic reading method of Code128 barcode based on global optimization. Background technique [0002] The Code128 barcode was launched in 1981. Because of its many characters and rich coding information, especially its advantages of short code length, allowing two-way scanning, automatic error correction, etc., it has been widely used in industries such as industry, logistics, and retail. Applications. [0003] In the Code128 coding rules, a module is represented by a black or white line of equal width, in which 1 to 4 consecutive modules of the same color form a character, and each character is divided into multiple black and white according to the established rules in the coding table. character. [0004] There are a total of 107 characters in the Code128 encoding table, except for the stop bit (STOP) which is composed of 13 modules (7 characters), other characters ...

Claims

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Application Information

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IPC IPC(8): G06K7/14G06F40/126
CPCG06K7/1413G06K7/1443
Inventor 曾欣科贾可王奥邓超李佩玮
Owner CHENGDU UNIV OF INFORMATION TECH
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