MHDT: A deep-learning-based text detection algorithm for unstructured data in banking

Shenglan MA, Lingling YANG, Hao WANG, Hong XIAO, Hong Ning DAI, Shuhan CHENG, Tongsen WANG

Research output: Book Chapters | Papers in Conference ProceedingsConference paper (refereed)Researchpeer-review

Abstract

Text detection in natural scene images becomes highly demanded for unstructured data in banking. In this paper, we propose a new deep learning algorithm called MSER, Hu-moment and Deep learning for Text detection (MHDT) based on Maximum Stable Extremal Regions (MSER) and Hu-moment features. Firstly, we extract MSERs as candidate characters. Secondly, a character classifier is introduced with Hu-moment features to reduce the number of input for clustering. After single linkage clustering, a text classifier trained from a Deep Brief Network is used to delete non-text. The proposed algorithm is evaluated on the ICDAR database, and the experimental results show that the proposed algorithm yields high precision and recall rate.

Original languageEnglish
Title of host publicationACM International Conference Proceeding Series
PublisherAssociation for Computing Machinery
Pages295-300
Number of pages6
ISBN (Print)9781450366007
DOIs
Publication statusPublished - 22 Feb 2019
Externally publishedYes
Event11th International Conference on Machine Learning and Computing, ICMLC 2019 - Zhuhai, China
Duration: 22 Feb 201924 Feb 2019

Publication series

NameACM International Conference Proceeding Series
VolumePart F148150

Conference

Conference11th International Conference on Machine Learning and Computing, ICMLC 2019
Country/TerritoryChina
CityZhuhai
Period22/02/1924/02/19

Bibliographical note

Funding Information:
This work is partially funded by the Fujian Fumin Foundation and is supported by the National Natural Science Foundation of China under Grant (No. 61672170 and No. 61871313), the Science and Technology Planning Project of Guangdong Province (No. 2017A050501035), and Science and Technology Program of Guangzhou (No. 201807010058).

Publisher Copyright:
© 2019 Copyright is held by the owner/author(s). Publication rights licensed to ACM.

Keywords

  • Deep learning
  • Text detection
  • Unstructured data

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