6.3.1 Improving Edges by Neighborhood Processing, Relaxation, Multi-Scale

Chapter Contents (Back)
Edges, Adaptive. Edges, Relaxation. Adaptive. Relaxation.

Zucker, S.W., Hummel, R.A., Rosenfeld, A.,
An Application of Relaxation Labeling to Line and Curve Enhancement,
TC(26), No. 4, April 1977, pp. 394-403. BibRef 7704
And: Correction: TC(26), pp. 922-929. BibRef

Zucker, S.W., Mohammed, J.L.,
A Hierarchical Relaxation System for Line Labeling and Grouping,
PRIP78(410-415). Edge Linking. Applied to lines and edges, two levels - assign oriented line segment labels, and consider the linking structure given by a specific model. The updating function is a bit different for the two relaxations, but both are the same basic form. BibRef 7800

Schachter, B.J., Lev, A., Zucker, S.W., and Rosenfeld, A.,
An Application of Relaxation to Edge Reinforcement,
SMC(7), 1977, pp. 813-816. BibRef 7700

Peleg, S., Rosenfeld, A.,
Determining Compatibility Coefficients for Curve Enhancement Relaxation Processes,
SMC(8), No. 7, 1978, pp. 548-555. BibRef 7800

Narayanan, K.A., O'Leary, D.P., Rosenfeld, A.[Azriel],
An Optimization Approach to Edge Reinforcement,
SMC(12), No. 4, July/August 1982, pp. 551-553. BibRef 8207

Ehrich, R.W., Schroeder, F.H.,
Contextual Boundary Formation by One-dimensional Edge Detection and Scan Line Matching,
CGIP(16), No. 2, June 1981, pp. 116-149.
Elsevier DOI BibRef 8106

Cooper, D.B., Elliot, H., Choen, F.S., and Symosek, P.F.,
Stochastic Boundary Estimation and Object Recognition,
CGIP(12), No. 4, April 1980, pp. 326-356.
Elsevier DOI BibRef 8004

Cooper, D.B., Elliot, H.,
A Maximum Likelihood Framework for Boundary Estimation,
PRIP78(25-31) BibRef 7800

Zabele, G.S., Koplowitz, J.,
On Improving Line Detection in Noisy Images,
CGIP(15), No. 2, February 1981, pp. 130-135.
Elsevier DOI BibRef 8102
Earlier: PRIP79(146-149). BibRef

Shanmugan, K.S., Paul, C.,
A Fast Edge Thinning Operator,
SMC(12), No. 4, July/August 1982, pp. 567-569. BibRef 8207

Paler, K., Kittler, J.V.,
Grey Level Edge Thinning: A New Method,
PRL(1), 1983, pp. 409-416. BibRef 8300

Lacroix, V.,
A Three-Module Strategy for Edge Detection,
PAMI(10), No. 6, November 1988, pp. 803-810.
IEEE DOI BibRef 8811
And: Reply to comments: PAMI(12), No. 2, February 1990, pp. 224. Compute edge strength, Generalized non-maximal deletion, Follow edges. BibRef

Lacroix, V.[Vinciane],
Color Line Detection,
CIAP11(I: 318-326).
Springer DOI 1109

Park, R.H., Choi, W.Y.,
Comments on 'A Three-Module Strategy for Edge Detection',
PAMI(12), No. 2, February 1990, pp. 223-224.
IEEE DOI BibRef 9002

Geman, D., Reynolds, G.,
Constrained Restoration and the Recovery of Discontinuities,
PAMI(14), No. 3, March 1992, pp. 367-383.
IEEE DOI Image restoration issues. BibRef 9203

Geman, D., Geman, S., Graffigne, C., and Dong, P.,
Boundary Detection by Constrained Optimization,
PAMI(12), No. 7, July 1990, pp. 609-628.
IEEE DOI Application of an iterative technique to refine the boundary point positions. BibRef 9007

Geman, D.[Donald],
Stochastic Model for Boundary Detection,
IVC(5), No. 2, May 1987, pp. 61-65.
Elsevier DOI BibRef 8705

Leung, E.[Eva], Li, X.B.[Xiao-Bo],
Parallel Processing Approaches To Edge Relaxation,
PR(21), No. 6, 1988, pp. 547-558.
Elsevier DOI BibRef 8800

Hancock, E.R., Kittler, J.V.,
Edge-Labeling Using Dictionary-Based Relaxation,
PAMI(12), No. 2, February 1990, pp. 165-181.
IEEE DOI BibRef 9002
A Label Error Process for Discrete Relaxation,
ICPR90(I: 523-528).
See also Combining Evidence in Probabilistic Relaxation. BibRef

Papachristou, P., Petrou, M., Kittler, J.V.,
Edge Postprocessing Using Probabilistic Relaxation,
SMC-B(30), No. 3, June 2000, pp. 383-402.
IEEE Top Reference. 0006
Earlier: A2, A1, A3:
Error propagation analysis for edge postprocessing,
ICIP96(I: 861-864).
Earlier: A3, A1, A2:
Combining Evidence in Dictionary Based Probabilistic Relaxation,
SCIA93(785-795). BibRef

Kittler, J.V., Papachristou, P., Petrou, M.,
Contextual Postprocessing for Line Detection,
SCIA93(1-2). BibRef 9300

Hancock, E.R., Haindl, M., Kittler, J.V.,
A Hierarchical Evidence Combining Edge Detection,
CIAP91(494-501). BibRef 9100

Hatef, M.[Mohamad], Kittler, J.V.[Josef V.],
Constraining probabilistic relaxation with symbolic attributes,
Springer DOI 9509

Hancock, E.R., Haindl, M., Kittler, J.V.,
Multiresolution Edge Labelling Using Hierarchical Relaxation,
IEEE DOI BibRef 9200

Hancock, E.R., Kittler, J.V.,
Relaxational Refinement of Intensity Ridges,
IEEE DOI BibRef 9200

Hancock, E.R.,
Resolving Edge-Line Ambiguities Using Probabilistic Relaxation,
IEEE DOI Edge suppression in line detection. BibRef 9300

Beymer, D.J.[David J.],
Finding Junctions Using the Image Gradient,
IEEE DOI BibRef 9100
And: MIT AI Memo-1266, December 1991.
WWW Link. Or:
PS File. Add junction detection to the standard edge detection. BibRef

Hadingham, P.T.,
Symbolic Description of Edges Using a Geometric Relaxation Technique,
PRL(7), 1988, pp. 173-179. BibRef 8800

Kundu, A., Mitra, S.K.,
A New Algorithm for Image Edge Extraction Using a Statistical Classifier Approach,
PAMI(9), No. 4, July 1987, pp. 569-577. BibRef 8707

Kundu, A.,
Robust Edge Detection,
PR(23), No. 5, 1990, pp. 423-440. BibRef 9000
Earlier: CVPR89(11-18).
IEEE DOI Improve the edge detector results by 2 steps of edge detection and supression of spurious edges. BibRef

Duncan, J.S., Birkholzer, T.,
Edge Reinforcement Using Parameterized Relaxation Labeling,
PAMI(14), No. 5, May 1992, pp. 502-515.
IEEE DOI BibRef 9205
Earlier: CVPR89(19-27).
IEEE DOI Relaxation applied to continuous output, e.g. direction with parameterized values (an oriented ellipse). BibRef

Tan, H.L., Gelfand, S.B., Delp, E.J.,
A Comparative Cost Function Approach to Edge Detection,
SMC(19), No. 6, Nov/Dec 1989, pp. 1337-1349. BibRef 8911

Tan, H.L., Gelfand, S.B., Delp, E.J.,
A Cost Minimization Approach to Edge Detection Using Simulated Annealing,
PAMI(14), No. 1, January 1992, pp. 3-18.
IEEE DOI BibRef 9201
Earlier: CVPR89(86-91).

Yoo, J.S., Bouman, C.A., Delp, E.J., Coyle, E.J.,
The Nonlinear Prefiltering and Differences of Estimates Approaches to Edge Detection: Applications of Stack Filters,
GMIP(55), No. 2, March 1993, pp. 140-yy. BibRef 9303

Yoo, J.S., Coyle, E.J., Bouman, C.A.,
Dual Stack Filters and the Modified Difference of Estimates Approach to Edge Detection,
IP(6), No. 12, December 1997, pp. 1634-1645.

Iyengar, S.S.[S. Sitharama], Deng, W.A.[Wei-An],
An Efficient Edge-Detection Algorithm Using Relaxation Labeling Technique,
PR(28), No. 4, April 1995, pp. 519-536.
Elsevier DOI BibRef 9504

Deng, W.A.[Wei-An], Iyengar, S.S.[S. Sitharama],
A New Probabilistic Relaxation Scheme and Its Application to Edge-Detection,
PAMI(18), No. 4, April 1996, pp. 432-437.
Dictionary scheme. BibRef

Chen, W.C., Thacker, N.A., Rockett, P.I.,
Adaptive Step-Edge Model for Self-Consistent Training of Neural-Network for Probabilistic Edge Labeling,
VISP(143), No. 1, February 1996, pp. 41-50. BibRef 9602

Bolton, A.G., Brown, S.F., Moran, W.,
A Computationally Efficient Algorithm for Enhancing Linear Features in Images,
PR(29), No. 12, December 1996, pp. 2017-2023.
Elsevier DOI 9701

Xie, M.,
Edge Linking by Using Causal Neighborhood Window,
PRL(13), 1992, pp. 647-656. BibRef 9200

Pedersini, F.[Federico], Sarti, A.[Augusto], Tubaro, S.[Stefano],
Improving the performance of edge localization techniques through error compensation,
SP:IC(12), No. 1, March 1998, pp. 33-47.
Elsevier DOI BibRef 9803

Petit, E., Lemoine, J., Djeziri, S.,
An adaptative method to smooth discrete curves proposed as a final step for edge detection,
IVC(19), No. 3, February 2001, pp. 145-152.
Elsevier DOI 0103

Tek, H.[Hüseyin], Kimia, B.B.[Benjamin B.],
Boundary Smoothing via Symmetry Transforms,
JMIV(14), No. 3, May 2001, pp. 211-223.
DOI Link 0106
Process the boundary to fill gaps and remove spurious points. Uses MAT or skeleton transformations. BibRef

Tek, H.[Huseyin], Kimia, B.B.[Benjamin B.],
Perceptual Organization via the Symmetry Map and Symmetry Transforms,
CVPR99(II: 471-477).
IEEE DOI BibRef 9900

Lu, D.S.[De-Sian], Chen, C.C.[Chien-Chang],
Edge detection improvement by ant colony optimization,
PRL(29), No. 4, 1 March 2008, pp. 416-425.
Elsevier DOI 0711
Edge detection; Ant colony optimization (ACO); Pheromone trail BibRef

Zhong, J.J.[Jing-Jing], Luo, S.W.[Si-Wei], Zou, Q.[Qi],
Visual Attention Guided Multi-Scale Boundary Detection in Natural Images for Contour Grouping,
IEICE(E92-D), No. 3, March 2009, pp. 555-558.
WWW Link. 0907
Pyramid based grouping. BibRef

Verma, O.P.[Om Prakash], Hanmandlu, M.[Madasu], Kumar, P.[Puneet], Chhabra, S.[Sidharth], Jindal, A.[Akhil],
A novel bacterial foraging technique for edge detection,
PRL(32), No. 8, 1 June 2011, pp. 1187-1196.
Elsevier DOI 1101
Ant Colony System; Bacterial foraging; Derivative; Direction probability matrix; Edge detection BibRef

Faghih, M.M.[Mohammad Mehdi], Moghaddam, M.E.[Mohsen Ebrahimi],
Neural gray edge: Improving gray edge algorithm using neural network,

Rajeswari, R., Rajesh, R.,
A modified ant colony optimization based approach for image edge detection,

Bergevin, R.[Robert], Bergeron, V.[Vincent],
Enhancing Boundary Primitives Using a Multiscale Quadtree Segmentation,
ISVC08(I: 45-54).
Springer DOI 0812

Bergevin, R.[Robert], Filiatrault, A.[Alexandre],
Enhancing Contour Primitives by Pairwise Grouping and Relaxation,
Springer DOI 0708

Zhou, L.X.[Ling-Xiang], Gu, W.K.[Wei-Kang],
1st and 2nd order recursive operators for adaptive edge detection,
Springer DOI 9709
A Fast Algorithm for Adaptive Edge Detection,
ICPR96(B71.1). 9608
(Zhejiang Univ., PRC) BibRef

Levy, M.,
A New Theoretical Approach to Relaxation, Application to Edge Detection,
ICPR88(I: 208-212).
IEEE DOI BibRef 8800

Chapter on Edge Detection and Analysis, Lines, Segments, Curves, Corners, Hough Transform continues in
Line Detectors, Direct Detection of Straight Lines .

Last update:Jan 30, 2024 at 20:33:16