Character defect detecting method of tire mold

Abstract

The invention discloses a character defect detecting method of a tire mold. The method comprises the following steps of S1, scanning the tire mold of a tire to be detected, collecting and obtaining a group of images, and obtaining the circular-arc-shaped profile of the outer side of the tire; S2, fitting the circle center and the radius of the circular-arc-shaped profile of the outer side of the tire, and then, positioning an image region of the tire mold of the tire as an ROI (region of interest) image to be tested; S3, classifying the ROI image; S4, selecting different methods for processing according to the classification of the ROI image, and obtaining a CAD (computer aided design) image block matched with each ROI image; S5, performing character recognition, and further performing defect judgment according to the character recognition result; S6, responding to the condition of the character defect existence judging result; returning the operation to execute the fourth step and the fifth step so as to select the judgment result with few character defects as the final result after secondary defect judgment. The character defect detecting method has the advantages that the detection stability is high; the detection cost is low; the detection accuracy is high; the false alarm rate is low; the application range is wide; the character defect detecting method can be widely applied to the field of tire mold detection.

Description

technical field [0001] The invention relates to the field of image processing, in particular to a character defect detection method of a tire mold. Background technique [0002] Glossary: [0003] ROI: RegionOfInterest, region of interest; [0004] NCC: NormalizedCrossCorrelation normalized cross-correlation. [0005] In the production of tire molds, quality inspection is particularly important, and character defect detection is an important work of quality inspection. At present, the defect detection of tire mold characters in the industry mainly relies on human eyes. However, the noisy factory environment, a large amount of inspection work and high requirements for quality inspection make it difficult to meet the demand solely by human eye detection. Machine vision is to use machines instead of human eyes to complete observation and judgment. It is often used in product quality inspection in the mass production process, or in dangerous environments that are not suitable...

AI Technical Summary

Problems solved by technology

However, this method mainly uses the information of large characters in the upper part of the image for matching and positioning. When there are no characters or only small characters in the upper part of the image, the result of matching and positioning will be wrong, and it is impossible to guarantee that all ROI images to be tested are correct. Accurate acquisition of matching CAD image blocks may result in large detection errors

Moreover, during character segmentation, for some densely distributed and relatively small characters, individual characters may be disconnected or glued to other characters during segmentation, causing false positives and detection errors

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