Abstract
English billboards are common in our daily work and life, and how to effectively recognize them is a problem worthy of study. This paper mainly uses Progressive Scale Expansion Network (PSENet) and Convolutional Recurrent Neural Network (CRNN) to conduct text recognition experiments on English billboards. The English billboards are divided into four categories: text distortion, larger background, special text font, and normal format. PSENet is used for text detection, and CRNN is used for text recognition. The identification results of PSENet and CRNN revealed differences among the four groups of English billboards: normal format text recognition is the best, and large background text recognition is the worst, and the recognition effect of text distortion and special text font is less accurate. Finally, the work of this paper is analyzed and summarized, and the future work is prospected.
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