A deformable template model based on fuzzy alignment algorithm

Z. Xue, D. Shen, E. K. Teoh

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

2 Scopus citations


A deformable template model for object extraction is proposed based on the fuzzy alignment algorithm (FAA). This object matching algorithm is partitioned into two iterative processes, the first is to estimate the pose relationship (point correspondence and transform parameters) between the current template and the prototype using FAA, the second is to adjust the current template under the exertion of internal energy and external energy functions. An affine-invariant internal energy function of the deformable template is utilized to deal with the transformation of the templates between different domains. Comparative studies with G-Snake model demonstrate the effectiveness of the proposed algorithm and show that it outperforms G-Snake in matching objects with large shearing of shapes.

Original languageEnglish
Title of host publicationIEEE International Conference on Image Processing
Number of pages4
StatePublished - Dec 1 2000
EventInternational Conference on Image Processing (ICIP 2000) - Vancouver, BC, Canada
Duration: Sep 10 2000Sep 13 2000


OtherInternational Conference on Image Processing (ICIP 2000)
CityVancouver, BC

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition
  • Hardware and Architecture
  • Electrical and Electronic Engineering


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