8.3.5 Other Complete Systems

Chapter Contents (Back)
Segmentation, Systems.

Milgram, D.L.[David L.], Kahl, D.J.[Daryl J.],
Recursive Region Extraction,
CGIP(9), No. 1, 1979, pp. 82-88.
Elsevier DOI Segmentation, Recursive. BibRef 7900

Wermser, D., Haussmann, G., Liedtke, C.E.,
Segmentation of Blood Smears by Hierarchical Thresholding,
CVGIP(25), No. 2, February 1984, pp. 151-168.
Elsevier DOI Segmentation, Thresholds. BibRef 8402

Haussmann, G., Liedtke, C.E.,
A Region Extraction Approach to Blood Smear Segmentation,
CVGIP(25), No. 2, February 1984, pp. 133-150.
Elsevier DOI BibRef 8402

Liedtke, C.E.,
Image Segmentation Considering Properties of the Human Visual System,
ISPDSA83(471-482). BibRef 8300

Celenk, M.[Mehmet],
A Color Clustering Technique for Image Segmentation,
CVGIP(52), No. 2, November 1990, pp. 145-170.
Elsevier DOI BibRef 9011
Earlier:
A Recursive Clustering Technique for Color Picture Segmentation,
CVPR88(437-444).
IEEE DOI Segmentation, Color. Clustering. Find clusters in cylinder sections of the histogram (hue and chroma). BibRef

Celenk, M.,
Analysis of Color Images of Natural Scenes,
JEI(4), No. 4, October 1995, pp. 382-396. BibRef 9510

Celenk, M.[Mehmet],
Color Scene Recognition Using Relational Distance Measurement,
SPIE(2727), March 1996, pp. 229-240. BibRef 9603

Celenk, M., Smith, S.H.,
Color Image Segmentation by Clustering and Parametric-Histogramming Technique,
ICPR86(883-886). BibRef 8600

Choo, A.P., Maeder, A.J., Pham, B.,
Image Segmentation for Complex Natural Scenes,
IVC(8), No. 2, May 1990, pp. 155-163.
Elsevier DOI BibRef 9005

Rignot, E., and Chellappa, R.,
Segmentation of Synthetic Aperture Radar Complex Data,
JOSA-A(8), September 1991, pp. 1499-1509. BibRef 9109

Rignot, E., Chellappa, R.,
Segmentation of Polarimetric Synthetic Aperture Radar Data,
IP(1), No. 3, July 1992, pp. 281-300.
IEEE DOI SAR Imagery. BibRef 9207

Rignot, E., Chellappa, R., and Dubois, P.,
Unsupervised Segmentation of Polarimetric SAR Data Using the Covariance Matrix,
GeoRS(30), July 1992, pp. 697-705. BibRef 9207

Rignot, E., and Chellappa, R.,
Maximum A Posteriori Classification of Multifrequency, Multilook Synthetic Aperture Radar Intensity Data,
JOSA-A(10), April 1993, pp. 573-582. BibRef 9304

Chellappa, R., Zelnio, E.G., and Rignot, E.,
Understanding Synthetic Aperature Radar Images,
DARPA92(229-245). Good overview of SAR. BibRef 9200

Mitiran, J., Bouillant, S., Bourennane, E.,
SVM approximation for real-time image segmentation by using an improved hyperrectangles-based method,
RealTimeImg(9), No. 3, June 2003, pp. 179-188.
Elsevier DOI 0310
BibRef

Zahara, E.[Erwie], Fan, S.K.S.[Shu-Kai S.], Tsai, D.M.[Du-Ming],
Optimal multi-thresholding using a hybrid optimization approach,
PRL(26), No. 8, June 2005, pp. 1082-1095.
Elsevier DOI 0506
BibRef

Fan, S.K.S.[Shu-Kai S.], Lin, Y.[Yen],
A multi-level thresholding approach using a hybrid optimal estimation algorithm,
PRL(28), No. 5, 1 April 2007, pp. 662-669.
Elsevier DOI 0703
Multi-level thresholding; Mixture Gaussian curve fitting; Expectation maximization (EM); Particle swarm optimization (PSO) BibRef

Fan, S.K.S.[Shu-Kai S.], Lin, Y.[Yen],
A fast estimation method for the generalized Gaussian mixture distribution on complex images,
CVIU(113), No. 7, July 2009, pp. 839-853.
Elsevier DOI 0905
Generalized Gaussian distribution (GGD); Shape parameter; Expectation maximization (EM); Particle swarm optimization (PSO); Moment matching estimator; Maximize likelihood estimator BibRef

Hamdaoui, F.[Fayšal], Ladgham, A.[Anis], Sakly, A.[Anis], Mtibaa, A.[Abdellatif],
A new images segmentation method based on modified particle swarm optimization algorithm,
IJIST(23), No. 3, 2013, pp. 265-271.
DOI Link 1309
particle swarm optimization BibRef

Hamdaoui, F.[Fayšal], Sakly, A.[Anis], Mtibaa, A.[Abdellatif],
FPGA implementation of particle swarm optimization based on new fitness function for MRI images segmentation,
IJIST(25), No. 2, 2015, pp. 139-147.
DOI Link 1506
segmentation BibRef

Ladgham, A.[Anis], Hamdaoui, F.[Fayšal], Sakly, A.[Anis], Mtibaa, A.[Abdellatif],
Fast MR brain image segmentation based on modified Shuffled Frog Leaping Algorithm,
SIViP(9), No. 5, July 2015, pp. 1113-1120.
Springer DOI 1506
BibRef

Mehmood, S.[Shahid], Cagnoni, S.[Stefano], Mordonini, M.[Monica], Khan, S.A.[Shoab Ahmad],
An embedded architecture for real-time object detection in digital images based on niching particle swarm optimization,
RealTimeIP(10), No. 1, March 2015, pp. 75-89.
Springer DOI 1503
BibRef

Cagnoni, S.[Stefano], Mordonini, M.[Monica], Sartori, J.[Jonathan],
Particle Swarm Optimization for Object Detection and Segmentation,
EvoIASP07(241-250).
Springer DOI 0704
BibRef

Mussi, L.[Luca], Cagnoni, S.[Stefano],
Artificial Creatures for Object Tracking and Segmentation,
EvoIASP08(xx-yy).
Springer DOI 0804
BibRef

Kayal, S.[Subhradeep],
Unsupervised image segmentation using the Deffuant-Weisbuch model from social dynamics,
SIViP(11), No. 8, November 2017, pp. 1405-1410.
WWW Link. 1710
BibRef


Levinkov, E.[Evgeny],
Scene Segmentation in Adverse Vision Conditions,
GCPR14(750-756).
Springer DOI 1411
BibRef

Fu, W.L.[Wen-Long], Johnston, M.[Mark], Zhang, M.J.[Meng-Jie],
A Hybrid Particle Swarm Optimisation with Differential Evolution Approach to Image Segmentation,
EvoIASP11(173-182).
Springer DOI 1104
BibRef

Taylor, C.J.[Camillo Jose],
Towards Fast and Accurate Segmentation,
CVPR13(1916-1922)
IEEE DOI 1309
Segmentation BibRef

Taylor, C.J.[Camillo J.], Cowley, A.[Anthony],
Fast Segmentation via Randomized Hashing,
BMVC09(xx-yy).
PDF File. 0909
Based on feature vector for pixel. BibRef

Sezgin, M., Sankur, B.,
Image multi-thresholding based on sample moment function,
ICIP03(II: 415-418).
IEEE DOI 0312
BibRef

Koch, I., Marshall, G.,
Bootstrap Coverage Plots for Image Segmentation,
ICPR96(II: 447-451).
IEEE DOI 9608
(The Univ. of Newcastle, AUS) BibRef

Cox, I.J., Rao, S.B., Zhong, Y.[Yu],
Ratio Regions: A Technique for Image Segmentation,
ICPR96(II: 557-564).
IEEE DOI 9608
(NEC Res. Institute Inc., USA) BibRef

Lee, C.H.,
Iterative Region Segmentation,
PRIP82(557-559). An experiment to see what is needed to segment a variety of types of objects (point, line, area). Nothing which isn't obvious. BibRef 8200

Sakaue, K.[Katsuhiko], and Takagi, M.[Mikio],
Image Segmentation by Iterative Method,
ICPR82(192-194). The paper talks around obvious issues and says nothing. BibRef 8200

Sakaue, K.[Katsuhiko], and Takagi, M.[Mikio],
Separation of Overlapping Particles by Iterative Method,
ICPR80(522-524). BibRef 8000

Priese, L., and Rehrmann, V.,
On Hierarchical Color Segmentation and Applications,
CVPR93(633-634).
IEEE DOI BibRef 9300

Chapter on 2-D Region Segmentation Techniques, Snakes, Active Contours continues in
Two-Dimensional Histogram Analysis for Segmentation .


Last update:Nov 18, 2017 at 20:56:18