High-speed dimension code positioning identification system based on full convolutional neural network

Abstract

The invention discloses a high-speed dimension code positioning identification system based on a full convolutional neural network. The invention discloses a high-speed dimension code positioning identification system based on a one-stage strategy full convolutional neural network. The high-speed dimension code positioning identification system comprises a data preparation module, a data enhancement module, a learning training module and a two-dimensional code detection positioning identification module. A feature extraction network of a two-dimensional code detection positioning identification module is set to be a combination of six convolution layers and five pooling layers; one pooling layer is arranged between every two convolution layers, the step length of each pooling layer is 2, the feature information of the dimension code is fully extracted to obtain a two-dimensional code feature map, and the position and the category of the input two-dimensional code are predicted in a regression mode on the output feature extraction map; and the identification system configuration of the next convolutional neural network to be tested is automatically adjusted and reconstructed according to the test effect of the network model, so that the real-time performance is enhanced. According to the positioning recognition system, the types and the position coordinates of one or more two-dimensional codes in the picture can be detected at the same time, the detection recognition precision is higher than 95%, and the detection speed is lower than 5 ms/frame.

Description

technical field [0001] The invention relates to the technical field of two-dimensional code identification, in particular to a high-speed two-dimensional code positioning and identification system based on a one-stage strategy fully convolutional neural network. Background technique [0002] In daily life and industrial applications, a two-dimensional code is used more and more widely. The prior art one-dimensional code recognition method locates the starting position of the one-dimensional code or the positioning pattern of the two-dimensional code through a full image search. However, for larger-sized images, such as courier bills, natural scenes or documents, etc., because one-dimensional codes account for a small proportion of the entire image, and because of the particularity of the scanning environment, reflections, dim light, etc. will affect The recognition accuracy and recognition speed of a two-dimensional code are missing or cannot be detected, which will affect t...

AI Technical Summary

Problems solved by technology

However, for larger-sized images, such as courier bills, natural scenes or documents, etc., because one-dimensional codes account for a small proportion of the entire image, and because of the particularity of the scanning environment, reflect...

Images