Industry Challenges and Needs
Tire sidewalls are marked with various raised or indented tire specifications, detailing the type and performance of the tire. These marks, along with the tread pattern, reflect the brand's image and characteristics to some extent. Sidewall information is created during the vulcanization process, where operators change molds or segments based on tire models to form the necessary vulcanization mold. This process can lead to human errors or wear of the segments, causing mismatches with the standard and quality issues in tire production. Therefore, inspecting the first tire's characters after vulcanization can verify mold accuracy, preventing significant production losses due to incorrect information in an entire batch. Currently, this inspection is mainly performed manually, which is time-consuming, lacks precision, and is prone to omissions.
Due to the three-dimensional nature of sidewall characters, 3D inspection can build upon 2D detection to extract three-dimensional information of the characters, making precise recognition of sidewall characters possible. Thus, applying 3D machine vision to the inspection of initial tire characters, by scanning the sidewall with a 3D laser sensor and employing image processing algorithms to extract character information, followed by comparing this information with standard templates using character recognition algorithms, can verify whether there are errors, omissions, unauthorized additions, or wear and tear in the sidewall text and patterns.
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