摘要
场景文字检测与识别是一种通用文字识别技术,已成为近年来计算机视觉与文档分析领域的热点研究方向.其被广泛应用于地理定位、车牌识别、无人驾驶等领域.相对于传统的文档文字检测和识别,场景文字在字体、尺度、排布、背景等方面变化更加剧烈,深度学习技术也由于卓越的性能成为该领域的主流方法.本文主要回顾了作者基于深度学习在此领域取得的代表性成果,并对此领域未来研究趋势进行了展望.
Scene text detection and recognition is a universal text recognition technology, which has become a hot research topic in the field of computer vision and document analysis in recent years. It is widely applied in geographical positioning, license plate recognition, and driverless applications. Compared to traditional document text detection and recognition, scene text varies more dramatically in font, color, scale, layout, and background.Owing to its excellent performance, deep learning has been widely adopted in this field. In this paper, we mainly review our representative studies based on deep learning in this field and describe the future research trends in this field.
作者
白翔
杨明锟
石葆光
廖明辉
Xiang BAI;Mingkun YANG;Baoguang SHI(Minghui LIAO School of Electronic Information and Communications, Huazhong University of Science and Technology, Wuhan 430074, Chin)
出处
《中国科学：信息科学》
CSCD
北大核心
2018年第5期531-544,共14页
Scientia Sinica(Informationis)
基金
国家自然科学基金(批准号:61733007
61222308
61573160)
数字出版技术国家重点实验室开放课题(批准号:F2016001)资助项目
