Study on Sign Language Recognition Fusion Algorithm Using FNN

  • Xiaoyi Yang
Conference paper

DOI: 10.1007/978-3-642-14880-4_68

Part of the Advances in Intelligent and Soft Computing book series (AINSC, volume 78)
Cite this paper as:
Yang X. (2010) Study on Sign Language Recognition Fusion Algorithm Using FNN. In: Cao B., Wang G., Guo S., Chen S. (eds) Fuzzy Information and Engineering 2010. Advances in Intelligent and Soft Computing, vol 78. Springer, Berlin, Heidelberg

Abstract

To overcome the limitation of hand shape recognition, the paper presented a recognition method of hand shape fusion based on the fuzzy neural network of BP. By means of fuzzy neural network of BP, the method analyzed the fusion computing for the collected hand gesture and lip shape image, viewed respectively the fusion image as the fuzzy set of hand gesture and lip shape, made the operation of fuzzy arithmetic operators for fuzzy set, matched the operation results and the sign of hand gesture and lip shape in database, carried on the fuzzy set operation for the gotten two sets of hand gesture and lip shape, finally got the recognition result. The simulation experiments show that the presented method is better in sign Language recognition, and it maybe has wide realistic application foreground in the education of deaf-and-dumb people.

Keywords

Education of deaf-and-dumb people BP fuzzy neural network Fusion computing Sign language recognition Hand gesture shape database Lip shape database 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Xiaoyi Yang
    • 1
    • 2
    • 3
  1. 1.College of Optoelectronic EngineeringChongqing UniversityChongqingChina
  2. 2.College of Education ScienceMunicipal Key Lab. of Chongqing for Special Children Psychology Consultation and EducationChongqingChina
  3. 3.Chongqing Normal UniversityChongqingChina

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