Abstract
For the purpose of solving the tough problem of the recognition of QR code which is marked on rough and highly reflective metal surface by laser, this work proposes a method of image processing based on multi-feature fusion. This method was requested to establish the integrated feature combined by color feature, texture feature and classify pixel points by means of k-means clustering, then optimize the image of QR code by morphology, Finally, this method was applied to the QR code Laser marking on the AL97 casting aluminum ingots to recognize, then compare with the accepted method OTSU algorithm, The experimental results show that the method is effective obviously.
Highlights
Considering the above situations, we select the aluminum ingot casting as the research object to propose QR code preprocessing method based on comprehensive feature clustering of color and texture in this paper. This method makes use of the combination of color feature and texture feature to compose comprehensive feature, and uses K-means clustering to a Corresponding author: 1130877605@qq.com classify pixel, the QR code images with low contrast, uneven light intensity and image noise are optimized by morphological method
We randomly selected one hundred laser marking QR images on Casting aluminum ingots to get the value of symbol contrast (SC) and analyse, statistics about SC illustrate that most of them quality grades is F for SC range from 0.02 to 0.15 and the QR images quality is too low to scan as Fig.[2]
QR code image processing could be considered as a segmentation between foreground and background
Summary
Remelting casting aluminum ingots is the common metal raw material in industry, and QR code on its’. As shown in Fig.[1], there are texture and high-reflection in image of QR code on the surface of remelting casting aluminum ingots,and noisy result from uneven surface. This phenomenon is common in casting metal material. According to the test method of QR image in bar code standards, the quality of QR image can be described by contrast. QR image contrast (C) is used as QR symbol contrast (SC), A graded standard of QR image quality is established according to SC as follows:. We randomly selected one hundred laser marking QR images on Casting aluminum ingots to get the value of SC and analyse, statistics about SC illustrate that most of them quality grades is F for SC range from 0.02 to 0.15 and the QR images quality is too low to scan as Fig.[2]
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