Script identification in the wild via discriminative convolutional neural network

作者：

Highlights：

• We study a new and important topic: script identification in scene text images.

• The proposed DiscCNN combines deep features and the mid-level representation.

• DiscCNN learns special characteristics of scripts from training data automatically.

• DiscCNN achieves state-of-the-art performances on scene, video and document scripts.

• A large-scale in-the-wild script identification dataset is proposed.

摘要

Highlights•We study a new and important topic: script identification in scene text images.•The proposed DiscCNN combines deep features and the mid-level representation.•DiscCNN learns special characteristics of scripts from training data automatically.•DiscCNN achieves state-of-the-art performances on scene, video and document scripts.•A large-scale in-the-wild script identification dataset is proposed.

论文关键词：Script identification,Convolutional neural network,Mid-level representation,Discriminative clustering,Dataset

论文评审过程：Received 25 May 2015, Revised 23 October 2015, Accepted 10 November 2015, Available online 1 December 2015, Version of Record 24 December 2015.

论文官网地址：https://doi.org/10.1016/j.patcog.2015.11.005