Knowledge Commons of Institute of Automation,CAS
Automatic Watermeter Digit Recognition on Mobile Devices | |
Gao, Yunze1,2; Zhao, Chaoyang1,2; Wang, Jinqiao1,2; Lu, Hanqing1,2 | |
2017 | |
会议名称 | International Conference on Internet Multimedia Computing and Service |
会议日期 | 2017.8.23-8.25 |
会议地点 | Qingdao,China |
摘要 | Automatic watermeter digit recognition in the wild is a challenging task, which is an application of scene text recognition in the field of computer vision. In this paper, we propose an automatic watermeter digit recognition approach on mobile devices which consists of digit detection and recognition. Specifically, we adopt Adaboost with aggregated channel features (ACF) to detect watermeter digital regions, where the computation is accelerated by the fast feature pyramid technology. Then a small attention bidirectional long short-term memory (BLSTM) is designed for end-to-end digit sequence recognition. Convolutional Neural network (CNN) is exploited to extract discriminative feature and BLSTM is able to capture the rich context in both directions within sequence data. Moreover, an attention mechanism is added to weight the most important part of incoming image features. We validate the performace of our approach on the collected complex dataset. It contains various watermeter images in real scenario which has illumination changes, messy environment, half-digit and blurring. It is observed that the proposed algorithm outperforms existing methods. Our approach runs 10 fps with 96.1% accuracy on HUAWEI Mate 8. |
语种 | 英语 |
文献类型 | 会议论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/20122 |
专题 | 紫东太初大模型研究中心_图像与视频分析 |
作者单位 | 1.National Laboratory of Pattern Recognition, Institute of Automation Chinese Academy of Sciences 2.University of Chinese Academy of Sciences |
第一作者单位 | 模式识别国家重点实验室 |
推荐引用方式 GB/T 7714 | Gao, Yunze,Zhao, Chaoyang,Wang, Jinqiao,et al. Automatic Watermeter Digit Recognition on Mobile Devices[C],2017. |
条目包含的文件 | 下载所有文件 | |||||
文件名称/大小 | 文献类型 | 版本类型 | 开放类型 | 使用许可 | ||
高云泽_Automatic Waterm(682KB) | 会议论文 | 开放获取 | CC BY-NC-SA | 浏览 下载 |
除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。
修改评论