Natural scene text detection based on multiscale connectionist text proposal network
Huang, Min 1Lan, Chaohao 1Huang, Wei 1Tao, Yang2
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作者信息
1. South China Univ Technol, Sch Software Engn, Guangzhou, Peoples R China
2. Guangzhou Robustel Ltd, Guangzhou, Peoples R China
折叠
Abstract
The technique of recognising text in natural scene pictures is widely used in social production. For the existing identification methods, it is difficult to accurately identify in complex environments. The accuracy of the detection determines the efficiency of the identification. A text detection method based on Multiscale Connectionist Text Proposal Network is proposed. The Multiscale-Region Proposal Network regresses and classifies the extracted region to obtain the final candidate region. Taking a large number of commodity image samples as a dataset, the multi-scale joint text proposal network is used to detect and locate the text content area in the image. The experimental results show that the proposed algorithm improves the detection accuracy in complex environments.
Key words
image classification/image segmentation/text detection/object detection/image colour analysis/edge detection/natural scenes/neural nets/feature extraction/text analysis/existing identification methods/complex environments/text detection method/multiscale connectionist text proposal network/Multiscale-Region Proposal Network regresses/multiscale joint text proposal network/text content area/detection accuracy/natural scene text detection/natural scene pictures
NETL
NSTL
Wiley