6.6 Other Edge Detector and Use Papers

Chapter Contents (Back)
Edges, Detectors - Basic.

Cooper, D.B.[David B.], Sung, F.P.[Francis P.],
Multiple-Window Parallel Adaptive Boundary Finding in Computer Vision,
PAMI(5), No. 3, May 1983, pp. 299-316. Divide the image into windows, find a boundary across the window, between the object and the background, merge the boundaries in adjacent windows. BibRef 8305

Cooper, D.B.[David B.], Sung, F.P.[Francis P.], Schenker, P.S.,
Toward a Theory of Multiple-Window Algorithms for Fast Adaptive Boundary Finding in Computer Vision,
ICPR80(1278-1284). BibRef 8000

de Souza, P.[Peter],
Edge Detection Using Sliding Statistical Tests,
CVGIP(23), No. 1, July 1983, pp. 1-14.
Elsevier DOI BibRef 8307

Selmane, M.K., Allen, C.R.,
Implementation of a Fast Programmable Edge Detection Preprocessor,
PRL(1), 1983, pp. 423-427. BibRef 8300

Bartliff, D.J.,
An Automatic Procedure for Image Segmentation,
PRL(1), 1983, pp. 435-442. BibRef 8300

Song, X., Neuvo, Y.,
Robust Edge Detection Based on Morphological Filters,
PRL(14), 1993, pp. 889-894. BibRef 9300

Wu, Q.M., Rodd, M.G.,
Fast Boundary Extraction for Industrial Inspection,
PRL(12), 1991, pp. 483-489. BibRef 9100

Seeger, U., Seeger, R.,
A Fast Algorithm for Encoding the Image Structure by Edge Directions,
PRL(12), 1991, pp. 611-617. BibRef 9100

Venkatesh, S., Owens, R.,
On the Classification of Image Features,
PRL(11), 1990, pp. 339-349. Gabor and three-point filters. BibRef 9000

Lalitha, L., Dutta Majumder, D.,
A New Linear Feature Detection Technique Based on Second Order Neighbors,
PRL(11), 1990, pp. 561-569. BibRef 9000

Poggio, T.[Tomaso], Voorhees, H.[Harry], Yuille, A.L.[Alan L.],
A Regularized Solution to Edge Detection,
Complexity(4), 1988, pp. xx-yy. BibRef 8800
Earlier: MIT AI Memo-833, April 1985.
WWW Link. BibRef

Kundu, M.K., Pal, S.K.,
Thresholding for Edge Detection Using Human Psychovisual Phenomena,
PRL(4), 1986, pp. 433-441. BibRef 8600

Sleigh, A.C.,
The Extraction of Boundaries Using Local Measures Driven by Rules,
PRL(4), 1986, pp. 247-258. BibRef 8600

Bennamoun, M., Boashash, B.,
A Probabilistic Approach for Automatic Parameters Selection for the Hybrid Edge Detector,
IEICE(E80-A), No. 8, August 1997, pp. 1423-1429. 9709

Chatterjee, N., Pal, P., Das, J.,
Boundary Extraction of Sodar Images,
SP(62), No. 2, October 1997, pp. 229-235. 9801

Deng, G., Pinoli, J.C.,
Differentiation-Based Edge-Detection Using the Logarithmic Image-Processing Model,
JMIV(8), No. 2, March 1998, pp. 161-180.
DOI Link 9803

See also Entropy Interpretation of the Logarithmic Image Processing Model With Application to Contrast Enhancement, An. BibRef

Deng, G.[Guang],
A Statistical Framework for Generalized Linear Image Processing Systems,
JMIV(58), No. 1, May 2017, pp. 2-26.
WWW Link. 1704

Chanda, B.[Bhabatosh], Kundu, M.K.[Malay K.], Padmaja, Y.V.[Y. Vani],
A Multiscale Morphologic Edge Detector,
PR(31), No. 10, October 1998, pp. 1469-1478.
Elsevier DOI 9808

Reveilles, J.P., Yaacoub, J.,
Maximum Area Triangle Operator For Edge-Detection,
JEI(6), No. 4, October 1997, pp. 406-414. 9807

Czerwinski, R.N., Jones, D.L., O'Brien, W.D.,
Line and Boundary Detection in Speckle Images,
IP(7), No. 12, December 1998, pp. 1700-1714.

Desolneux, A.[Agnès], Moisan, L.[Lionel], Morel, J.M.[Jean-Michel],
Edge Detection by Helmholtz Principle,
JMIV(14), No. 3, May 2001, pp. 271-284.
DOI Link 0106

See also grouping principle and four applications, A. BibRef

Abraham, I., Abraham, R., Desolneux, A.[Agnès], Te, S.L.T.[Sebastien Li-Thiao],
Significant edges in the case of non-stationary Gaussian noise,
PR(40), No. 11, November 2007, pp. 3277-3291.
Elsevier DOI 0707
Edge detection; Significant edges; Inverse problem; Statistical hypothesis testing BibRef

Sun, G.Y.[Gen-Yun], Liu, Q.H.[Qin-Huo], Liu, Q.A.[Qi-Ang], Ji, C.Y.[Chang-Yuan], Li, X.W.[Xiao-Wen],
A novel approach for edge detection based on the theory of universal gravity,
PR(40), No. 10, October 2007, pp. 2766-2775.
Elsevier DOI 0707
Edge detection; Image processing; The law of universal gravity BibRef

Lopez-Molina, C.[Carlos], Bustince, H., Fernandez, J., Couto, P., de Baets, B.[Bernard],
A gravitational approach to edge detection based on triangular norms,
PR(43), No. 11, November 2010, pp. 3730-3741.
Elsevier DOI 1008
Triangular norm; Edge detection; Image processing BibRef

Lopez-Molina, C.[Carlos], de Baets, B.[Bernard], Bustince, H.,
Generating fuzzy edge images from gradient magnitudes,
CVIU(115), No. 11, November 2011, pp. 1571-1580.
Elsevier DOI 1110
Edge detection; Image processing; Fuzzy image processing BibRef

Lopez-Molina, C.[Carlos], de Baets, B.[Bernard], Bustince, H.,
Quantitative error measures for edge detection,
PR(46), No. 4, April 2013, pp. 1125-1139.
Elsevier DOI 1301
Edge detection; Image processing; Performance evaluation BibRef

Lopez-Molina, C., Galar, M., Bustince, H., de Baets, B.,
On the impact of anisotropic diffusion on edge detection,
PR(47), No. 1, 2014, pp. 270-281.
Elsevier DOI 1310
Image regularization BibRef

Lopez-Molina, C., Bustince, H., de Baets, B.,
Separability Criteria for the Evaluation of Boundary Detection Benchmarks,
IP(25), No. 3, March 2016, pp. 1047-1055.
edge detection BibRef

Wang, G.[Gang], Lopez-Molina, C.[Carlos], de Baets, B.[Bernard],
Multiscale Edge Detection Using First-Order Derivative of Anisotropic Gaussian Kernels,
JMIV(61), No. 8, October 2019, pp. 1096-1111.
Springer DOI 1909

Wang, G.[Gang], de Baets, B.[Bernard],
Contour detection based on anisotropic edge strength and hierarchical superpixel contrast,
SIViP(13), No. 8, November 2019, pp. 1657-1665.
WWW Link. 1911

Su, Z.[Zhuo], Liu, W.Z.[Wen-Zhe], Yu, Z.T.[Zi-Tong], Hu, D.[Dewen], Liao, Q.[Qing], Tian, Q.[Qi], Pietikäinen, M.[Matti], Liu, L.[Li],
Pixel Difference Networks for Efficient Edge Detection,
Convolutional codes, Training, Image segmentation, Image edge detection, Semantics, Memory management, Detectors, Vision applications and systems BibRef

Liu, Y.[Yun], Cheng, M.M.[Ming-Ming], Hu, X.W.[Xiao-Wei], Bian, J.W.[Jia-Wang], Zhang, L.[Le], Bai, X.[Xiang], Tang, J.H.[Jin-Hui],
Richer Convolutional Features for Edge Detection,
PAMI(41), No. 8, August 2019, pp. 1939-1946.
Image edge detection, Feature extraction, Detectors, Training, Computer architecture, Task analysis, richer convolutional features BibRef

Liu, Y.[Yun], Cheng, M.M.[Ming-Ming], Hu, X.W.[Xiao-Wei], Wang, K.[Kai], Bai, X.[Xiang],
Richer Convolutional Features for Edge Detection,
Same title, slightly different authors. Feature extraction, Image color analysis, Image edge detection, Lead, Machine, learning BibRef

Singh, K.K., Bajpai, M.K., Pandey, R.K.,
A Novel Approach for Edge Detection of Low Contrast Satellite Images,
DOI Link 1504

Mittal, A.[Ajay], Sofat, S.[Sanjeev], Hancock, E.R.[Edwin R.], Mousset, S.[Stéphane],
A Statistical Operator for Detecting Weak Edges in Low Contrast Images,
ICIAR12(I: 89-96).
Springer DOI 1206

Touqir, I.[Imran], Saleem, M.[Muhammad],
Novel Edge Detector,
Springer DOI 0804

Chartier, S., Lepage, R.,
Learning and extracting edges from images by a modified Hopfield neural network,
ICPR02(III: 431-434).

Lee, M., Leung, S., Pun, T., Cheung, H.,
Edge Detection by Genetic Algorithm,
ICIP00(Vol I: 478-480).

Song, Y.W.[Young-Won], Udpa, S.S.[Satish S.],
A New Edge Detection Algorithm Using Data Fusion Approaches,
IEEE Abstract. BibRef 9900

Lai, G.C.[George C.], de Figueiredo, R.J.P.[Rui J.P.],
Robust Extraction of Low Contrast Edges using Clustering-based Segmentation and Refinement,
IEEE Abstract. BibRef 9900

Liu, S.S., Twu, J.H., Wang, S.J.,
Image Representation Using Curvature Information in Intensity Profiles,
ICIP97(II: 720-723).

Lorca, F., Kessal, L., Demigny, D.,
Efficient ASIC and FPGA Implementations of IIR Filters for Real Time Edge Detection,
ICIP97(II: 406-409).
IEEE DOI BibRef 9700

Wright, A., Acton, S.,
Watershed Pyramids for Edge Detection,
ICIP97(II: 578-581).
IEEE DOI BibRef 9700

Wang, S., Ziou, D., Benie, G.B.,
A Competitive and Cooperative Neural Network for Line Detection,
International Conferenceon Neural Network and its Applications, 1995, pp. 304-307. Neural networks. BibRef 9500

Ziou, D.,
Noise Estimation from Step Edge Operator Responses,
SCIA93(1397-1402). Noise Estimation. BibRef 9300

Healey, G.[Glenn], Sanz, J.L.C.[Jorge L.C.],
CONTAM: An Edge-Based Approach to Segmenting Images with Irregular Objects,
CVPR85(485-490). (IBM San Jose), How it is better is not clear. Classification into two classes. BibRef 8500

Richards, W.A., Nishihara, H.K., Dawson, B.,
CARTOON: A Biologically Motivated Edge Detection Algorithm,
MIT AI Memo-668, June 1982. BibRef 8206

Geuen, W.,
A Fast Edge Detection Algorithm Matching Visual Contour Perception,
ISPDSA83(483-492). BibRef 8300

Chapter on Edge Detection and Analysis, Lines, Segments, Curves, Corners, Hough Transform continues in
Computation of Edges in Range, Depth or Multi-Dimensional Data .

Last update:Jul 18, 2024 at 20:50:34