Intelligent recognition of English fuzzy text and teaching based on parallel projection and region expansion

Abstract

Abstract The most important and difficult point of English fuzzy text is how to effectively improve boundary segmentation and character classification. Traditional fuzzy text recognition models are often difficult to accurately identify the characteristics of fuzzy English text. In order to improve the effect of English fuzzy text recognition, based on machine learning technology, this paper combines parallel projection and region expansion technology to construct an English fuzzy text intelligent recognition system. Moreover, based on the idea of region growth, this paper expands the triangular facets of the same processing area onto the same plane, then recalculates the associated texture points, and uses the rotation and translation method to wrap the two-dimensional vector texture on the surface of the three-dimensional model, which effectively solves the problem of entanglement of the two-dimensional vector map on the three-dimensional model when the texture information is insufficient, and realizes the intelligent recognition of fuzzy English characters with the support of the intelligent database. In addition, this paper designs a controlled experiment to analyze the recognition effect. The research results show that the model constructed in this paper works well.