Decoding method and system for ultra-low-contrast two-dimension code
A decoding method and two-dimensional code technology, applied in the direction of electromagnetic radiation induction, etc., can solve the problems of poor image processing effect, inability to separate the two-dimensional code graphics from the background, etc., and achieve the effect of good processing effect.
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[0035] Example 1
[0036] figure 1 This is a flowchart of the method for decoding an ultra-low contrast two-dimensional code in this embodiment. The method for decoding an ultra-low-contrast two-dimensional code includes the following steps:
[0037] 1) Establish the integral image of the original image of the QR code, and use the integral image to perform adaptive binarization of the original image of the QR code;
[0038] 2) Perform median filtering on the original image of the QR code after binarization to denoise;
[0039] 3) Locate the original image of the QR code after denoising;
[0040] 4) Error detection, correction and decoding of the extracted binary series.
[0041] Any point (x, y) of the integral image in step 1) represents the sum of gray levels from the upper left corner of the original image to all the points in the rectangular area formed by this point, namely
[0042]
[0043] among them, Represents the integral image, and i(x',y') represents the original image. It c...
Example Embodiment
[0055] Example 2
[0056] The difference between the decoding method of the ultra-low-contrast two-dimensional code in this embodiment and the first embodiment is that the implementation of the integral image of the original image of the two-dimensional code in step 1) is optimized in this embodiment. Greatly save the memory resources of the device and improve the operating efficiency of the device.
[0057] The establishment of the integral image of the original image of the QR code is achieved through the following steps:
[0058] i. Create two new arrays with the same width as the original image of the QR code;
[0059] ii. When processing pixels (x, y), in the two arrays of step i, record the y-s-1th row and the y+sth row of the integral image respectively, where s is an integer;
[0060] iii. Use the following formula to calculate the sum of pixels in the pixel point (x, y) window area (2s+1)×(2s+1), the formula is:
[0061] Where x 1 =x-s; x 2 =x+s; y 1 =y-s; y 2 =y+s, I(x 2 , Y ...
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