DocumentCode
2006293
Title
A Gaussian mixture model for edge-enhanced images with application to sequential edge detection and linking
Author
Cook, Gregory W. ; Delp, Edward J.
Author_Institution
Video & Image Process. Lab., Purdue Univ., West Lafayette, IN, USA
Volume
2
fYear
1998
fDate
4-7 Oct 1998
Firstpage
540
Abstract
We present a new stochastic model for pixels in an edge-enhanced image. The model is robust because it allows for the possibilities of false and multiple edges, and may be efficiently estimated using a expectation-maximization technique with a minimum description length metric. The direct applicability of the model for the sequential edge linking algorithm is investigated
Keywords
Gaussian processes; edge detection; image enhancement; optimisation; Gaussian mixture model; edge-enhanced image; edge-enhanced images; expectation-maximization technique; false edges; minimum description length metric; multiple edges; pixels; robust model; sequential edge detection; sequential edge linking algorithm; stochastic model; Application software; Density functional theory; Image edge detection; Image processing; Joining processes; Laboratories; Pixel; Signal to noise ratio; Statistics; Stochastic processes;
fLanguage
English
Publisher
ieee
Conference_Titel
Image Processing, 1998. ICIP 98. Proceedings. 1998 International Conference on
Conference_Location
Chicago, IL
Print_ISBN
0-8186-8821-1
Type
conf
DOI
10.1109/ICIP.1998.723501
Filename
723501
Link To Document