An improved algorithm for segmenting and recognizing connected handwritten characters

Xiaoyu Zhao, Zheru Chi, Dagan Feng

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

4 Citations (Scopus)

Abstract

In this paper, an improved algorithm is proposed for the segmentation and recognition of handwritten character strings. In the method, a gradient descent mechanism is used to weigh the distance measure in applying KNN for segmenting/recognizing connected characters (numerals and Chinese characters) in the left-to-right scanning direction. In recognizing connected characters, a high quality segmentation technique is essential. Conventional approaches attempt to separate the string into individual characters without recognition and apply a recognition algorithm onto each isolated character, resulting improper segmentation and poor recognition results in many situations. Our proposed algorithm simulates the human beings's process in recognizing connected character strings where segmentation and recognition is mingled with each other. Experimental results on 1959 character strings from the USPS database of postal envelopes show that the algorithm works robustly and efficiently.
Original languageEnglish
Title of host publication11th International Conference on Control, Automation, Robotics and Vision, ICARCV 2010
Pages1611-1615
Number of pages5
DOIs
Publication statusPublished - 1 Dec 2010
Event11th International Conference on Control, Automation, Robotics and Vision, ICARCV 2010 - Singapore, Singapore
Duration: 7 Dec 201010 Dec 2010

Conference

Conference11th International Conference on Control, Automation, Robotics and Vision, ICARCV 2010
Country/TerritorySingapore
CitySingapore
Period7/12/1010/12/10

Keywords

  • Character recognition
  • Connected handwritten character
  • Segmentation-recognition
  • String segmentation

ASJC Scopus subject areas

  • Artificial Intelligence
  • Control and Systems Engineering

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