计算机工程与应用2024，Vol.60Issue(9)：228-236,9.DOI:10.3778/j.issn.1002-8331.2301-0074
文本核重建与扩展实现任意形状文本检测
Text Kernel Reconstruction and Expansion for Arbitrary Shape Text Detection
摘要
Abstract
Segmentation-based methods approaches for pixel-level text prediction in natural scenes have demonstrated significant improvement in the detection of arbitrary shape text.However,the separation of adjacent text remains a chal-lenge in text detection.One common method for addressing this issue involves the use of text kernels,which are obtained by shrinking the annotation boundaries,to separate adjacent instances.While this approach is effective in certain scenarios,it discards a significant amount of information outside the text kernel,which can degrade the performance of segmentation-based text detection methods.To address this limitation,a text kernel reconstruction algorithm is proposed that postpones the generation of text kernels to the post-processing stage.The proposed approach utilizes the direction field predicted by the network to inwardly contract text instances,resulting in the formation of text kernels.Additionally,a text kernel expan-sion algorithm is proposed to restore full text instances from the resulting text kernels.Experiments on the Total-Text,CTW-1500,and MSRA-TD500 datasets show that the proposed method achieves similar or superior detection perfor-mance compared to the state-of-the-art(88.66%,87.28%,and 90.65%respectively).关键词
场景文本检测/任意形状/文本核Key words
scene text detection/arbitrary shape/text kernel分类
信息技术与安全科学引用本文复制引用
邓胜军,陈念年..文本核重建与扩展实现任意形状文本检测[J].计算机工程与应用,2024,60(9):228-236,9.基金项目
四川省科技厅重点研发项目(2021YFG0031) （2021YFG0031）
四川省省级科研院所科技成果转化项目(22YSZH0021). （22YSZH0021）
