A wavelet transform and SOFM based certificate image compression method

Xueming Qian, Hong Zhu, Ruirui Ji, Qieshi Zhang, Kun Yang

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

1 Citation (Scopus)

Abstract

A compression method is proposed based on the wavelet transform and self-organizing feature mapping (SOFM) neural network, in order to store the certificate image into the two-dimensional barcode, and at the same time, hold the image quality which must satisfy the requirement of true or false identification under high compression rate. The different sub-band coefficients of wavelet transform are quantized by SOFM with different quantization levels. The high efficient compression of the identification (ID) Card image is gained using an adaptive resolution combination method based on sub-block clustering encoding which encodes the sub-band coefficients after quantization. The experimental results show that this method has higher performance than JPEG.

Original languageEnglish
Title of host publicationProceedings of the World Congress on Intelligent Control and Automation (WCICA)
Pages4101-4104
Number of pages4
Volume5
Publication statusPublished - 2004
Externally publishedYes
EventWCICA 2004 - Fifth World Congress on Intelligent Control and Automation, Conference Proceedings - Hangzhou
Duration: 2004 Jun 152004 Jun 19

Other

OtherWCICA 2004 - Fifth World Congress on Intelligent Control and Automation, Conference Proceedings
CityHangzhou
Period04/6/1504/6/19

Keywords

  • 2D Barcode
  • Adaptive resolution
  • Image compression
  • SOFM neural network
  • Wavelet transform

ASJC Scopus subject areas

  • Control and Systems Engineering

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