Schachter, B.J.[Bruce J.],
Davis, L.S.[Larry S.],
Rosenfeld, A.[Azriel],
Some Experiments in Image Segmentation by Clustering
of Local Feature Values,
PR(11), No. 1, 1979, pp. 19-28.
Elsevier DOI
BibRef
7900
Earlier:
Scene Segmentation by Cluster Detection in Color Space,
UMD-CS TR-424, 1975.
Segmentation, Histogram.
Color.
Histograms, Multi-Dimensional.
Segmentation, Color. Multi-dimensional histograms to find color clusters.
BibRef
Ahuja, N.,
Rosenfeld, A.,
A Note on the Use of Second-Order Gray Level Statistics
for Threshold Selection,
SMC(8), 1978, pp. 895-898.
BibRef
7800
Ahuja, N.[Narendra],
Rosenfeld, A.[Azriel],
Haralick, R.M.[Robert M.],
Neighbor Gray Levels as Features in Pixel Classification,
PR(12), No. 4, 1980, pp. 251-260.
Elsevier DOI
BibRef
8000
Kirby, R.,
Rosenfeld, A.,
A Note on the Use of (Gray Level, Average Gray Level) Space as an
Aid in Threshold Selection,
SMC(9), 1979, pp. 860-864.
BibRef
7900
Kitchen, L.[Leslie],
Pietikainen, M.[Matti],
Rosenfeld, A.[Azriel], and
Wang, C.Y.[Cheng-Ye],
Multispectral Image Smoothing Guided by Global Distribution
of Pixel Values,
SMC(13), 1983, pp. 626-631.
Basically
the superspike algorithm extended to 2-D histograms (red-green).
See also Image Segmentation by Texture Using Pyramid Node Linking.
BibRef
8300
Narayanan, K.A., and
Rosenfeld, A.,
Image Smoothing by Local Use of Global Information,
SMC(11), No. 12, December 1981, pp. 826-831.
Smoothing. Each pixel is averaged with only those neighbors which are (1) more
probable (higher value in histogram) and (2) in the same peak - no
concavity between the two. Applied iteratively, this produces
spikes where peaks formerly appeared. Superspike algorithm.
BibRef
8112
Pietikainen, M.[Matti], and
Rosenfeld, A.[Azriel],
Multispectral Image Smoothing by Local Use of Global Information,
UMDTR 1113, 1981.
BibRef
8100
Westman, T.,
Harwood, D.A.,
Laitinen, T., and
Pietikainen, M.,
Color Segmentation by Hierarchical Connected Components
Analysis with Image Enhancements by Symmetric Neighborhood Filters,
ICPR90(I: 796-802).
IEEE DOI Use the images, but do not cite Ohlander.
BibRef
9000
Moring, I.[Ilkka], and
Pietikainen, M.[Matti],
Experiments with Histogram Guided Image Smoothing,
EE Dept.,
Univ. of OuluOulu Finland, 1982.
Further work on the super spike smoothing algorithm.
BibRef
8200
Wang, C.Y.[Cheng-Ye], and
Kitchen, L.[Leslie],
Improvements in Multispectral Image Smoothing,
UMD-CS TR-1152, DAAG-53-76C-1038, March 1982.
Extensions of the earlier 2-D histogram superspike method.
BibRef
8203
Werman, M.[Michael],
Peleg, S.[Shmuel],
Rosenfeld, A.[Azriel],
Werman, M.,
Peleg, S., and
Rosenfeld, A.,
A Distance Metric for Multidimensional Histograms,
CVGIP(32), No. 3, December 1985, pp. 328-336.
Elsevier DOI
BibRef
8512
Abutaleb, A.S.[Ahmed S],
Automatic Thresholding of Grey-Level Pictures
Using Two-Dimensional Entropy,
CVGIP(47), No. 1, July 1989, pp. 22-32.
Elsevier DOI Threshold based on maximum entropy using the 2-D histogram of the
image.
BibRef
8907
Jain, A.K.,
Newman, T.S.,
Goulish, M.,
Range-Intensity Histogram for Segmenting LADAR Images,
PRL(13), 1992, pp. 41-56.
See also Model-Based Classification of Quadric Surfaces.
BibRef
9200
Li, L.Y.[Li-Yuan],
Gong, R.[Ran],
Chen, W.N.[Wei-Nan],
Gray-Level Image Thresholding Based on Fisher Linear Projection
of 2-Dimensional Histogram,
PR(30), No. 5, May 1997, pp. 743-749.
Elsevier DOI
9705
BibRef
Cheng, H.D.,
Chen, Y.H.[Yen-Hung],
Fuzzy partition of two-dimensional histogram and its application to
thresholding,
PR(32), No. 5, May 1999, pp. 825-843.
Elsevier DOI
BibRef
9905
Cheng, H.D.[Heng D.],
Chen, Y.H.[Yen-Hung],
Thresholding Based on Fuzzy Partition of Two-Dimensional Histogram,
ICPR98(Vol II: 1616-1618).
IEEE DOI
9808
BibRef
Cheng, H.D.,
Chen, Y.H.,
Jiang, X.H.,
Thresholding Using Two-Dimensional Histogram and Fuzzy Entropy
Principle,
IP(9), No. 4, April 2000, pp. 732-735.
IEEE DOI
0004
BibRef
Chang, J.H.[Jeng-Horng],
Fan, K.C.[Kuo-Chin],
Chang, Y.L.[Yang-Lang],
Multi-modal gray-level histogram modeling and decomposition,
IVC(20), No. 3, March 2002, pp. 203-216.
Elsevier DOI
0202
BibRef
Clément, A.,
Vigouroux, B.,
Unsupervised segmentation of scenes containing vegetation (Forsythia)
and soil by hierarchical analysis of bi-dimensional histograms,
PRL(24), No. 12, August 2003, pp. 1951-1957.
Elsevier DOI
0304
BibRef
Wang, L.S.[Li-Sheng],
Bai, J.[Jing],
Threshold selection by clustering gray levels of boundary,
PRL(24), No. 12, August 2003, pp. 1983-1999.
Elsevier DOI
0304
Consider threshold in continuous image space.
BibRef
Doignon, C.,
Graebling, P.,
de Mathelin, M.,
Real-time segmentation of surgical instruments inside the abdominal
cavity using a joint hue saturation color feature,
RealTimeImg(11), No. 5-6, October-December 2005, pp. 429-442.
Elsevier DOI
0510
BibRef
Xiao, Y.[Yang],
Cao, Z.G.[Zhi-Guo],
Zhang, T.X.[Tian-Xu],
Entropic thresholding based on gray-level spatial correlation histogram,
ICPR08(1-4).
IEEE DOI
0812
BibRef
Müller, W.[Wolfgang],
Henrich, A.[Andreas],
Faster Exact Histogram Intersection on Large Data Collections Using
Inverted VA-Files,
CIVR04(455-463).
Springer DOI
0505
BibRef
Chapter on 2-D Region Segmentation Techniques, Snakes, Active Contours continues in
Histogram Analysis for Threshold Selection and Segmentation .