Search results for key=SqC2000 : 1 match found.

Search my entire BibTeX database
Output format: Text
BibTeX entry
     Combine using:

Abstract icon Abstract BibTeX icon BibTeX entry Postscript icon Postscript PDF icon PDF PPT icon Powerpoint

Refereed full papers (journals, book chapters, international conferences)


  • @article{SqC2000,
    	vgclass =	{refpap},
    	vgproject =	{nn,invariance},
    	author =	{David McG. Squire and Terry M. Caelli},
    	title =	{Invariance Signatures: Characterizing contours by their
    	departures from invariance},
    	journal =	{Computer Vision and Image Understanding},
    	volume =	{77},
    	number =	{3},
    	pages =	{284--316},
    	month =	{March},
    	year =	{2000},
    	doi =	{},
    	url =	{/publications/postscript/1999/SquireCaelli_cviu99.pdf},
    	url1 =	{/publications/postscript/1999/},
    	abstract =	{In this paper, a new invariant feature of two-dimensional
    	contours is reported: the Invariance Signature. The Invariance
    	Signature is a measure of the degree to which a contour is invariant
    	under a variety of transformations, derived from the theory of Lie
    	transformation groups. It is shown that the Invariance Signature is
    	itself invariant under shift, rotation and scaling of the contour.
    	Since it is derived from local properties of the contour, it is
    	well-suited to a neural network implementation. It is shown that a
    	Model-Based Neural Network (MBNN) can be constructed which computes the
    	Invariance Signature of a contour, and classifies patterns on this
    	basis.  Experiments demonstrate that Invariance Signature networks can
    	be employed successfully for shift-, rotation- and scale-invariant
    	optical character recognition.},