S. Prabu, K. Joseph Abraham Sundar*
Intelligent Automation & Soft Computing, Vol.35, No.2, pp. 2071-2086, 2023, DOI:10.32604/iasc.2023.029105
Abstract Recognizing irregular text in natural images is a challenging task in computer vision. The existing approaches still face difficulties in recognizing irregular text because of its diverse shapes. In this paper, we propose a simple yet powerful irregular text recognition framework based on an encoder-decoder architecture. The proposed framework is divided into four main modules. Firstly, in the image transformation module, a Thin Plate Spline (TPS) transformation is employed to transform the irregular text image into a readable text image. Secondly, we propose a novel Spatial Attention Module (SAM) to compel the model to concentrate on text regions and obtain… More >
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