Method, device and equipment for detecting and recognizing tire mold character, and storage medium

Abstract

The invention discloses a method, a device and equipment for detecting and recognizing a tire mold character and a storage medium. The method comprises: inputting a sample of a collected tire mold picture data set into an improved SSD detection network for training, and establishing a character detection model; using a convolutional neural network to extract a feature vector of a character regionimage detected by a character detection model and inputting the feature vector into a long and short time memory network for training to establish a character recognition model; performing target detection on a character detection region of a to-be-detected tire mold image by the character detection model; and outputting a recognition result of a large character or a small character string in thecharacter region by the character recognition model. In the character detection stage, the detection model is established for the characteristics of the tire mold, so as to achieve high detection precision on the mold image. In the character recognition stage, the features are fused in the long and short time memory network after being extracted, and the recognition model is established to realizenon-split and quick recognition of a large character and a small string of an indefinite character length.

Description

technical field [0001] The invention relates to the technical field of image processing, in particular to a tire mold character detection and recognition method, device, equipment and storage medium. Background technique [0002] The character identification carried on the surface of the tire mold usually reflects some performance and characteristics of the rubber tire on the vulcanization molding line. The characters on its surface are concave characters generated by engraving, so the visual imaging is the image generated by the reflection difference between the character area and the background area. This makes it difficult to select and control the light source when collecting tire mold pictures, so that the collected pictures have characteristics such as uneven grayscale, broken character strokes, and indistinct grayscale differences from the background, which bring great difficulties to the detection and recognition of tire mold characters. big difficulty. [0003] In...

AI Technical Summary

Problems solved by technology

However, manual detection is not only inefficient, time-consuming and labor-intensive, but also easily causes visual fatigue of the staff, resulting in recognition errors

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