Regular Articles

Detecting text in natural scene images with conditional clustering and convolution neural network

[+] Author Affiliations
Anna Zhu, Guoyou Wang, Yangbo Dong

Huazhong University of Science and Technology, State Key Lab for Multispectral Information Processing Technology, School of Automation, 1037 Luoyu Road, Wuhan 430074, China

Brian Kenji Iwana

Kyushu University, Human Interface Laboratory, Information Science and Electrical Engineering, Nishi-ku, Fukuoka-shi 8190395, Japan

J. Electron. Imaging. 24(5), 053019 (Sep 29, 2015). doi:10.1117/1.JEI.24.5.053019
History: Received March 18, 2015; Accepted September 8, 2015
Text Size: A A A

Abstract.  We present a robust method of detecting text in natural scenes. The work consists of four parts. First, automatically partition the images into different layers based on conditional clustering. The clustering operates in two sequential ways. One has a constrained clustering center and conditional determined cluster numbers, which generate small-size subregions. The other has fixed cluster numbers, which generate full-size subregions. After the clustering, we obtain a bunch of connected components (CCs) in each subregion. In the second step, the convolutional neural network (CNN) is used to classify those CCs to character components or noncharacter ones. The output score of the CNN can be transferred to the postprobability of characters. Then we group the candidate characters into text strings based on the probability and location. Finally, we use a verification step. We choose a multichannel strategy to evaluate the performance on the public datasets: ICDAR2011 and ICDAR2013. The experimental results demonstrate that our algorithm achieves a superior performance compared with the state-of-the-art text detection algorithms.

Figures in this Article
© 2015 SPIE and IS&T

Citation

Anna Zhu ; Guoyou Wang ; Yangbo Dong and Brian Kenji Iwana
"Detecting text in natural scene images with conditional clustering and convolution neural network", J. Electron. Imaging. 24(5), 053019 (Sep 29, 2015). ; http://dx.doi.org/10.1117/1.JEI.24.5.053019


Access This Article
Sign in or Create a personal account to Buy this article ($20 for members, $25 for non-members).

Some tools below are only available to our subscribers or users with an online account.

Related Content

Customize your page view by dragging & repositioning the boxes below.

Related Book Chapters

Topic Collections

PubMed Articles
Advertisement
  • Don't have an account?
  • Subscribe to the SPIE Digital Library
  • Create a FREE account to sign up for Digital Library content alerts and gain access to institutional subscriptions remotely.
Access This Article
Sign in or Create a personal account to Buy this article ($20 for members, $25 for non-members).
Access This Proceeding
Sign in or Create a personal account to Buy this article ($15 for members, $18 for non-members).
Access This Chapter

Access to SPIE eBooks is limited to subscribing institutions and is not available as part of a personal subscription. Print or electronic versions of individual SPIE books may be purchased via SPIE.org.