关键词: 二维编码, 目标识别, SSD算法, Tensorflow

Abstract:

In order to realize two-dimensional coding and fit for machine and human reading, a new two-dimensional image coding technology combining two-dimensional coded images is proposed. According to the characteristics of the two-dimensional coded image without location identification, the target recognition algorithm is adopted to recognize the two-dimensional coding image, while improving the SSD（Single Shot Multibox Detector）algorithm to make it suitable for such target recognition. According to the recognition characteristics of small targets, the algorithm removes the original empty convolution layer and selects the shallow layer for feature fusion, and achieves the effect of accurate recognition of two-dimensional coded image. In addition, the depth learning platform based on the GTX1080 model is built, and a network learning and verification method is proposed, which trains network by generating corresponding data sets by computer, and verifies network separately by using the synthesized data set and real pictures. The test results show that the trained network by the proposed method has a coding recognition accuracy of 100% for real pictures with good photographing conditions.

Key words: two-dimensional coded, target recognition, Single Shot Multibox Detector（SSD）, Tensorflow