6.1.9 Facet Model for Edge Detection

Chapter Contents (Back)
Facet Model. ; Edges, Facet Model. See also The Facet Model for Descriptions.

Haralick, R.M., and Watson, L.T.,
A Facet Model for Image Data,
CGIP(15), No. 2, February 1981, pp. 113-129.
WWW Link. Compared in: See also Edge Detection and Linear Feature Extraction Using a 2-D Random Field Model. See also Edge and Region Analysis for Digital Image Data. BibRef 8102

Haralick, R.M.,
Second Directional Derivative Zero Crossing Detector Using the Cubic Facet Model,
CVPR85(672-677). One dimensional results are presented. BibRef 8500

Haralick, R.M., and Lee, J.S.J.[James S.J.],
Context Dependent Edge Detection and Evaluation,
PR(23), No. 1/2, 1990, pp. 1-19. BibRef 9000
Earlier:
WWW Link.
Context Dependent Edge Detection,
CVPR88(223-228).
IEEE DOI BibRef
And: ICPR88(I: 203-207).
IEEE DOI Edges, Evaluation. Use the best interpretation based on all edge directions through a pixel (or something like that). BibRef

Lee, J.S., Haralick, R.M., Shapiro, L.G.,
Morphologic Edge Detection,
RA(3), 1987, pp. 142-156. BibRef 8700

Matalas, I.[Ioannis], Benjamin, R.[Ralph], Kitney, R.[Richard],
An Edge-Detection Technique Using the Facet Model and Parameterized Relaxation Labeling,
PAMI(19), No. 4, April 1997, pp. 328-341.
IEEE DOI 9705
BibRef
Earlier:
Edge Detection and Curve Enhancement Using the Facet Model and Parameterized Relaxation Labeling,
ICPR94(A:1-5).
IEEE DOI First a variant of the cubic facet model detects the location, orientation and curvature of the edge. Then relaxation cleans it up, and maximizes connected contours. BibRef

Li, C.H., Tam, P.K.S.,
A global energy approach to facet model and its minimization using weighted least-squares algorithm,
PR(33), No. 2, February 2000, pp. 281-293.
WWW Link. 0001
BibRef

Ji, Q.A.[Qi-Ang], Haralick, R.M.[Robert M.],
Efficient facet edge detection and quantitative performance evaluation,
PR(35), No. 3, March 2002, pp. 689-700.
WWW Link. 0201
BibRef

Ji, Q.A.[Qi-Ang], Haralick, R.M.[Robert M.],
Quantitative Evaluation of Edge Detectors Using the Minimum Kernel Variance Criterion,
ICIP99(II:705-709).
IEEE Abstract. BibRef 9900


Worthington, P.L.,
Enhanced Canny edge detection using curvature consistency,
ICPR02(I: 596-599).
IEEE DOI 0211
BibRef

Sher, D.B.[David B.],
Tunable Facet Model Likelihood Generators for Boundary Pixel Detection,
CVWS87(35-40). BibRef 8700
And:
Generating Robust Operators from Specialized Ones,
CVWS87(301-303). BibRef
Earlier:
Optimal Likelihood Generators for Edge Detection under Gaussian Additive Noise,
CVPR86(94-99). The facet model is used and can be adjusted for various properties in the data. BibRef

Chapter on Edge Detection and Analysis, Lines, Segments, Curves, Corners, Hough Transform continues in
Evaluation of Edge Detection Algorithms .


Last update:Sep 25, 2017 at 16:36:46