Highly-accurate fast candidate reduction method for Japanese/Chinese character recognition

Ryosuke Odate, Hideaki Goto

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

A high-speed pattern matching algorithm is required for developing real-time character recognition applications especially for mobile devices with limited computational performances. Multilingual scene text recognition has recently become more important for mobile and wearable devices. Since Japanese and Chinese have thousands of characters, not only the accuracy but also the speed of classifiers are crucial. We formalized the candidate reduction technique for the Nearest Neighbor (NN) search with high-dimensional feature vectors, and proposed a tree-based clustering method to realize a fast handwritten character recognition. It works fine with ETL9B dataset consisting of Japanese handwritten characters and HCL2000 Chinese handwritten character dataset. In this paper, we propose an improved candidate reduction method based on our former one. The experimental results show that our method is 60.48% faster and more accurate than the former method.

Original languageEnglish
Title of host publication2016 IEEE International Conference on Image Processing, ICIP 2016 - Proceedings
PublisherIEEE Computer Society
Pages2886-2890
Number of pages5
ISBN (Electronic)9781467399616
DOIs
Publication statusPublished - 2016 Aug 3
Event23rd IEEE International Conference on Image Processing, ICIP 2016 - Phoenix, United States
Duration: 2016 Sep 252016 Sep 28

Publication series

NameProceedings - International Conference on Image Processing, ICIP
Volume2016-August
ISSN (Print)1522-4880

Other

Other23rd IEEE International Conference on Image Processing, ICIP 2016
CountryUnited States
CityPhoenix
Period16/9/2516/9/28

Keywords

  • Approximate Nearest Neighbor (ANN) search
  • Fast Nearest Neighbor search
  • Linear Discriminant Analysis (LDA)
  • Multilingual OCR
  • Real-time character recognition

ASJC Scopus subject areas

  • Software
  • Computer Vision and Pattern Recognition
  • Signal Processing

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