6.4.4 General Systems for Lines and Curves

Chapter Contents (Back)
Edge Linking. Lines, General. Curves, General.

Chaikin, G.M.[George Merrill],
An Algorithm For High Speed Curve Generation,
CGIP(3), No. 4, December 1974, pp. 346-349.
Elsevier DOI BibRef 7412

Riesenfeld, R.F.,
On Chaikin's algorithm,
CGIP(4), No. 3, September 1975, pp. 304-310.
Elsevier DOI 0501
Formulate as parameterized recursive function. Relate to B-Splines.
See also Algorithm For High Speed Curve Generation, An. BibRef

Shlien, S.[Seymour], Allard, P.[Paul],
A FIR filtering approach for the generation of smooth curves on a graphics terminal,
CGIP(17), No. 3, November 1981, pp. 269-280.
Elsevier DOI 0501
BibRef

Ramer, U., Ballard, D.H.,
Strip Trees: A Hierarchical Representation for Curves,
CACM(24), No. 5, May 1981, pp. 310-321. BibRef 8105
And: Correction: CACM(25), No. 3, March 1982, pp. 213. The strip is a rectangle that contains the curve in the given straight line section. This allows for more efficient intersection and membership tests since strips can be tested first. BibRef

Ballard, D.H.,
Strip Trees: A Hierarchical Representation for Map Features,
PRIP79(278-285). BibRef 7900
And: DARPA79(121-133). BibRef

Stockman, G.C., Kanal, L.N.,
Problem Reduction Representation for the Linguistic Analysis of Waveforms,
PAMI(5), No. 3, May 1983, pp. 287-298. BibRef 8305

Hoffman, D.D., Richards, W.A.,
Parts of Recognition,
Cognition(18), 1985, pp. 65-96. BibRef 8500
And: RCV87(227-242). BibRef
And: MIT AI Memo-732, December 1983. A discussion of how humans partition curves and shapes and a proposal that it will work for object recognition. BibRef

Singh, M., Seyranian, G., Hoffman, D.D.,
Parsing silhouettes: The short-cut rule,
PandP(61), 1999, pp. 636-660. BibRef 9900

Safaee-Rad, R., Tchoukanov, I., Smith, K.C., Benhabib, B.,
Constraints on Quadratic-Curved Features under Perspective Projection,
IVC(10), No. 8, October 1992, pp. 532-548.
Elsevier DOI BibRef 9210

Safaee-Rad, R., Tchoukanov, I., Benhabib, B., Smith, K.C.,
Accurate Parameter Estimation of Quadratic Curves from Grey-Level Images,
CVGIP(54), No. 2, September 1991, pp. 259-274.
Elsevier DOI BibRef 9109
Earlier: A1, A4, A3, Only:
Accurate estimation of elliptical shape parameters from a grey-level image,
ICPR90(II: 20-26).
IEEE DOI 9208
BibRef

Horn, B.K.P., Weldon, Jr., E.J.,
Filtering Closed Curves,
PAMI(8), No. 5, September 1986, pp. 665-668. BibRef 8609
Earlier: CVPR85(478-484). (MIT) Represent as radius of curvature vs. tangent direction. Derives various processing techniques, adding curves, and smoothing. BibRef

Tsai, W.H.[Wen-Hsiang],
Moment-preserving thresolding: A new approach,
CVGIP(29), No. 3, 1985, pp. 377-393.
Elsevier DOI 0501
BibRef

Chen, L.H.[Ling-Hwei], Tsai, W.H.[Wen-Hsiang],
Moment-Preserving Curve Detection,
SMC(18), 1988, pp. 148-158. BibRef 8800

Chen, L.H.[Ling-Hwei], Tsai, W.H.[Wen-Hsiang],
Moment-Preserving Line Detection,
PR(21), No. 1, 1988, pp. 45-53.
Elsevier DOI BibRef 8800

Walters, D.[Deborah],
Selection of Image Primitives for General-Purpose Visual Processing,
CVGIP(37), No. 2, February 1987, pp. 261-298.
Elsevier DOI BibRef 8702
Earlier:
Selection and Use of Image Features for Segmentation of Boundary Images,
CVPR86(319-324). BibRef

Chen, D.S.,
A Data-Driven Intermediate Level Feature Extraction Algorithm,
PAMI(11), No. 7, July 1989, pp. 749-758.
IEEE DOI Fit curves to edge data without linking, etc. BibRef 8907

Günther, O.[Oliver], Wong, E.[Eugene],
The Arc Tree: An Approximation Scheme to Represent Arbitrary Curved Shapes,
CVGIP(51), No. 3, September 1990, pp. 313-337.
Elsevier DOI The curve is broken in half at each level of the tree, not at any interest point. BibRef 9009

Wang, L.[Li], Pavlidis, T.[Theo],
Detection of Curved and Straight Segments from Gray-Scale Topography,
CVGIP(58), No. 3, November 1993, pp. 352-365.
DOI Link BibRef 9311

Liang, P.[Ping], Lee, J.F.[Jeng-Feng], Wang, Y.F.[Yuan-Fang],
Orientation-based Unique Representation for Planar Curves and Shapes,
VC(8), 1992, pp. 191-199. BibRef 9200

Lam, L.T.S., Lam, W.C.Y., Leung, D.N.K.,
A Knowledge-Based Boundary Convergence Algorithm for Line Detection,
PRL(15), No. 4, April 1994, pp. 383-392. BibRef 9404

Dori, D., Haralick, R.M.[Robert M.],
A Pattern-Recognition Approach to the Detection of Complex Edges,
PRL(16), No. 5, May 1995, pp. 517-529. BibRef 9505

Nishida, H.[Hirobumi],
Curve Description Based on Directional Features and Quasi-Convexity Concavity,
PR(28), No. 7, July 1995, pp. 1045-1051.
Elsevier DOI BibRef 9507

Nishida, H.[Hirobumi], Mori, S.,
Structural Analysis and Description of Curves by Quasi-Topological Features and Singular Points,
SDIA92(xx-yy). BibRef 9200

Viero, T., Jeulin, D.,
Morphological Extraction of Line Networks from Noisy Low-Contrast Images,
JVCIR(6), No. 4, December 1995, pp. 335-347. BibRef 9512

Wu, K.N., Levine, M.D.,
2D Shape Segmentation: A New Approach,
PRL(17), No. 2, February 8 1996, pp. 133-140. Related 3d:
See also 3D Part Segmentation: A New Physics-Based Approach. BibRef 9602

Zhu, Q.M.[Qiu-Ming],
Efficient Evaluations of Edge-Connectivity and Width Uniformity,
IVC(14), No. 1, February 1996, pp. 21-34.
Elsevier DOI 9608
Evaluation, Edges. Edges, Evaluation. Connectivity. Similar to
See also Edge Evaluation using Local Edge Coherence. BibRef

Zhu, Q.M., Payne, M., Riordan, V.,
Edge Linking by a Directional Potential Function (DPF),
IVC(14), No. 1, February 1996, pp. 59-70.
Elsevier DOI 9608
BibRef

Babaguchi, N.[Noboru], Aibara, T.[Tsunehiro],
Curvedness of a Line Picture,
PR(20), No. 3, 1987, pp. 273-280.
Elsevier DOI BibRef 8700

Zunic, J.,
A Coding Scheme for Certain Sets of Digital Curves,
PRL(16), 1995, pp. 97-104. BibRef 9500

Hsu, J.C.[Jui-Chi], Hwang, S.Y.[Shu-Yuen],
A Machine Learning Approach for Acquiring Descriptive Classification Rules of Shape Contours,
PR(30), No. 2, February 1997, pp. 245-252.
Elsevier DOI 9704
BibRef

Kocic, L.M., Milovanovic, G.V.,
Shape-Preserving Approximations by Polynomials and Splines,
CompMathApp(33), No. 11, June 1997, pp. 59-97. 9708
BibRef

Kudo, M.[Mineichi], Toyama, J.[Jun], Shimbo, M.[Masaru],
Multidimensional curve classification using passing-through regions,
PRL(20), No. 11-13, November 1999, pp. 1103-1111. 0001
BibRef

Streekstra, G.J., van den Boomgaard, R.[Rein], Smeulders, A.W.M.,
Scale Dependency of Image Derivatives for Feature Measurement in Curvilinear Structures,
IJCV(42), No. 3, May-June 2001, pp. 177-189.
DOI Link 0108
BibRef

Streekstra, G.J., van den Boomgaard, R.[Rein], Smeulders, A.W.M.,
Scale Dependent Differential Geometry for the Measurement of Center Line and Diameter in 3D Curvilinear Structures,
ECCV00(I: 856-870).
Springer DOI 0003
BibRef

Streekstra, G.J., Smeulders, A.W.M., van den Boomgaard, R.,
Tracing of Curvilinear Structures in 3D Images with Single Scale Diameter Measurement,
ScaleSpace99(501-506). BibRef 9900

Geusebroek, J.M.[Jan-Mark], Smeulders, A.W.M.[Arnold W.M.], Geerts, H.[Hugo],
A Minimum Cost Approach for Segmenting Networks of Lines,
IJCV(43), No. 2, July 2001, pp. 99-111.
DOI Link 0108
BibRef

Tang, Y.Y.[Yuan Y.], Yang, F.[Feng], Liu, J.M.[Ji-Ming],
Basic Processes of Chinese Character Based on Cubic B-Spline Wavelet Transform,
PAMI(23), No. 12, December 2001, pp. 1443-1448.
IEEE DOI 0112
For character compression, type descriptions, etc. Describe contour as b-spline, use wavelet to get control points for different resolutions. BibRef

Huo, X., Chen, J.,
JBEAM: Multiscale Curve Coding via Beamlets,
IP(14), No. 11, November 2005, pp. 1665-1677.
IEEE DOI 0510
BibRef

Piegl, L.A.[Les A.], Ma, W.Y.[Wei-Yin], Tiller, W.[Wayne],
An alternative method of curve interpolation,
VC(21), No. 1-2, February 2005, pp. 104-117.
Springer DOI 0502
BibRef

Ganguly, P.[Pankaj],
Modified Arc tree based hierarchical representation of digital curve,
PRL(27), No. 6, 15 April 2006, pp. 529-535.
Elsevier DOI 0604
Digital curve; Hierarchical representation; Arc tree; Split points; ISE BibRef

Berlemont, S.[Sylvain], Olivo-Marin, J.C.[Jean-Christophe],
Combining Local Filtering and Multiscale Analysis for Edge, Ridge, and Curvilinear Objects Detection,
IP(19), No. 1, January 2010, pp. 74-84.
IEEE DOI 1001
BibRef

Berlemont, S.[Sylvain], Bensimon, A.[Aaron], Olivo-Marin, J.C.[Jean-Christophe],
Feature-Adapted Fast Slant Stack,
ICIP07(IV: 57-60).
IEEE DOI 0709
Radon transform detecting features along curves.
See also JBEAM: Multiscale Curve Coding via Beamlets.
See also Fast slant stack: A notion of radon transform for data on a cartesian grid which is rapidly computable, algebraically exact, geometrically faithful, and invertible. BibRef

Manousopoulos, P.[Polychronis], Drakopoulos, V.[Vassileios], Theoharis, T.[Theoharis],
Parameter Identification of 1D Recurrent Fractal Interpolation Functions with Applications to Imaging and Signal Processing,
JMIV(40), No. 2, June 2011, pp. 162-170.
WWW Link. 1103
To model irregular data. BibRef

Kawase, H.[Hotaka], Shinya, M.[Mikio], Shiraishi, M.[Michio],
A Line Smoothing Method of Hand-Drawn Strokes Using Adaptive Moving Average for Illustration Tracing Tasks,
IEICE(E95-D), No. 11, November 2012, pp. 2704-2709.
WWW Link. 1211
BibRef

Wu, G.[Gang], Zhang, Y.C.[Yan-Chun],
A new Chebyshev polynomials descriptor applicable to open curves,
PRL(62), No. 1, 2015, pp. 41-48.
Elsevier DOI 1507
Chebyshev polynomial BibRef

Mathlouthi, Y.[Yosra], Mitiche, A.[Amar], Ben Ayed, I.[Ismail],
Regularised differentiation for image derivatives,
IET-IPR(11), No. 5, April 2017, pp. 310-316.
DOI Link 1706
BibRef

Milaghardan, A.H.[Amin Hosseinpoor], Abbaspour, R.A.[Rahim Ali], Claramunt, C.[Christophe],
A Geometric Framework for Detection of Critical Points in a Trajectory Using Convex Hulls,
IJGI(7), No. 1, 2018, pp. xx-yy.
DOI Link 1801
BibRef

Kimia, B.B.[Benjamin B.], Li, X.Y.[Xiao-Yan], Guo, Y.L.[Yu-Liang], Tamrakar, A.[Amir],
Differential Geometry in Edge Detection: Accurate Estimation of Position, Orientation and Curvature,
PAMI(41), No. 7, July 2019, pp. 1573-1586.
IEEE DOI 1906
Image edge detection, Detectors, Geometry, Kernel, Convolution, Topology, Histograms, Edge detection, differential geometry, topology BibRef

Sánchez-García, E.[Elena], Balaguer-Beser, Á.[Ángel], Almonacid-Caballer, J.[Jaime], Pardo-Pascual, J.E.[Josep Eliseu],
A New Adaptive Image Interpolation Method to Define the Shoreline at Sub-Pixel Level,
RS(11), No. 16, 2019, pp. xx-yy.
DOI Link 1909
BibRef

Xu, X.[Xun], Nguyen, M.C.[Manh Cuong], Yazici, Y.[Yasin], Lu, K.K.[Kang-Kang], Min, H.[Hlaing], Foo, C.S.[Chuan-Sheng],
SemiCurv: Semi-Supervised Curvilinear Structure Segmentation,
IP(31), 2022, pp. 5109-5120.
IEEE DOI 2208
Image segmentation, Roads, Task analysis, Semisupervised learning, Correlation, Biomedical imaging, Training, semantic segmentation BibRef

Canêjo, M.J.[Marcos José], Barros-de Mello, C.A.[Carlos Alexandre],
Edge Detection in Natural Scenes Inspired by the Speed Drawing Challenge,
IJIG(23), No. 1 2023, pp. 2350009.
DOI Link 2302
BibRef

Sun, Z.[Zhuang], Chen, L.[Li], Feng, Z.[Zhida], Liu, X.M.[Xiao-Ming],
B-Walk: Bernoulli Principle Guided Biased Random Walk for Curve Connection,
ICIP24(1445-1451)
IEEE DOI 2411
Image segmentation, Fluids, Accuracy, Energy exchange, Probability, Bernoulli principle, random walk, curve structure, curve reconnection BibRef

Challoob, M.[Mohsin], Gao, Y.S.[Yong-Sheng],
Quadratic Tensor Anisotropy Measures for Reliable Curvilinear Pattern Detection,
ACIVS20(139-150).
Springer DOI 2003
BibRef

Le Quentrec, É.[Étienne], Mazo, L.[Loïc], Baudrier, É.[Étienne], Tajine, M.[Mohamed],
Local Turn-Boundedness: A Curvature Control for a Good Digitization,
DGCI19(51-61).
Springer DOI 1905
BibRef