A review on image segmentation techniques

Pattern Recognition

Volumn 26, Issue 9, 1993, Pages 1277-1294

  Pal, Nikhil R ^a   Pal, Sankar K ^a  

^a INDIAN STATISTICAL INSTITUTE   (India)

Author keywords

Clustering; Edge detection; Fuzzy sets; Image segmentation; Markov Random Field; Relaxation; Thresholding

Indexed keywords

COLOR IMAGE PROCESSING; FUZZY SETS; MAGNETIC RESONANCE IMAGING; MATHEMATICAL MODELS; NEURAL NETWORKS; PARALLEL PROCESSING SYSTEMS; PATTERN RECOGNITION; PROBABILITY; STATISTICAL METHODS;

CLUSTERING; EDGE DETECTION; IMAGE SEGMENTATION; MARKOV RANDOM FIELDS; RELAXATION ALGORITHMS; THRESHOLDING;

IMAGE ANALYSIS;

EID: 0027658896     PISSN: 00313203     EISSN: None     Source Type: Journal    
DOI: 10.1016/0031-3203(93)90135-J     Document Type: Article

References (179)

1. Picture segmentation by directed split and merge procedure
2. An iterative thresholding algorithm for image segmentation
3. Image model Poisson distribution and object extraction
4. Segmentation using variable surface fitting
5. Theory of edge detection
6. Automatic boundary detection of the left-ventricle from cineangiograms
7. Some experiments on variable thresholding
8. A new method for image segmentation
9. Range image segmentation based on differential geometry a hybrid approach
10. Integration of edge and region based techniques for range image segmentation
11. Segmentation based on measures of contrast, homogeneity, and region size
12. Thresholding for edge detection using human psychovisual phenomena
13. A survey on image segmentation
14. Operations useful for similarity-invariant pattern recognition
15. An automated apparatus for cancer preprocessing CYBEST
16. Analysis of natural scenes
17. Scene segmentation techniques for the analysis of routine bone marrow smears from acute lymphoblastic leukemia patients
18. Detection of homogeneous regions by structural analysis
19. A structural analyzer for a class of textures
20. Localization of cellular structures
21. Syntactic algorithms for image segmentation and a special computer architecture for image processing
22. A spatial clustering procedure for multi-image data
23. A multi-spectral approach for scene analysis of cervical cytology smears
24. Image segmentation by unsupervised clustering and its applications
25. Edge and curve detection for visual scene analysis
26. Edge and curve detection further experiments
27. An operator which locates edges in digital pictures
28. Survey, image segmentation techniques
29. Edge and region analysis for digital image data
30. Zero-crossing of second directional derivative edge operator
31. Boundary and object detection in real world image
32. A modular computer vision system for picture segmentation and interpretation
33. Experiments in segmentation using a facet model region grower
34. Segmentation of pictures and maps through functional approximations
35. Nonsupervised crop classification through airborne multispectral observations
36. A survey of thresholding techniques
37. An amplitude sedimentation method based on the distribution function of an image
38. Automatic multithreshold selection
39. A segmentation system based on thresholding
40. Segmentation of document images
41. Object-background segmentation using new definitions of entropy
42. Entropic thresholding
43. A new method for gray level picture thresholding using the entropy of histogram
44. Region extraction by averaging and thresholding
45. Locating object boundaries in textured environments
46. A threshold selection method from gray level histograms
47. A note on the use of second order gray level statistics for threshold selection
48. Pixel classification on gray level and local “Busyness”
49. Threshold selection using quadtrees
50. Segmentation of muscle cell pictures: a preliminary study
51. Methodologies in pattern recognition and image analysis: a brief survey
52. A spatial thresholding method for image segmentation
53. Thresholding using relaxation
54. Entropy: a new definition and its applications
55. Gray level thresholding of images using a correlation criterion
56. Minimum error thresholding
57. Picture thresholding using an iterative selection method
58. Entropic thresholding: a new approach
59. A new method for gray level picture thresholding using the entropy of the histogram
60. Survey, image analysis and computer vision
61. Segmentation using contrast and homogeneity measures
62. Object background classification some new techniques
63. A gray level threshold selection method based on maximum entropy principle
64. Object background classification using a new definition of entropy
65. On object-background classification
66. Survey of threshold selection techniques
67. Iterative histogram modification
68. Iterative histogram modification
69. Threshold evaluation techniques
70. Gray level thresholding using second-order statistics
71. On image enhancement and threshold selection using the gray level co-occurrence matrix
72. Image segmentation and image models
73. Histogram modification for threshold selection
74. Automatic thresholding of gray level pictures using two-dimensional entropy
75. Automatic target classification using moment invariants of image shapes, Farnborough, U.K.
76. Segmentation and classification of range images
77. Use of range and reflectance data to find planar surface region
78. A maximum-likelihood approach to segmenting range data
79. Variable pyramid structures for image segmentation
80. Hierarchy in picture segmentation a stepwise optimization approach
81. Split and link algorithm for image segmentation
82. Low level segmentation of multispectral images via agglomerative clustering of uniform neighbours
83. Segmentation of natural scene
84. Image segmentation by syntactic method
85. Image smoothing and segmentation by multiresolution pixel linking further experiments and extensions
86. A syntactic method for image segmentation and object recognition
87. Image segmentation by semantic method
88. Scene labeling by relaxation operations
89. Dynamic measurement of computer generated image segmentation
90. A new probabilistic relaxation scheme
91. Edge detection and linear feature extraction using a 2-D random field model
92. An average edge detector
93. Two new edge detectors
94. Optimal edge detector design I: parameter selection and noise effects
95. Optimal edge detector design II: coefficient quantization
96. Digital step edges from zero crossing of second directional derivatives
97. A study of edge detection algorithms
98. An approach to edge detection based on the direction of edge elements
99. A computational approach to edge detection
100. Behavior of edges in scale space
101. Gray level edge thinning: a new method
102. Generalized threshold selection for edge detection
103. A survey of edge detection techniques
104. Edge detection by computer using planning
105. Preprocessing and feature extraction of picture patterns
106. Edge detection with iteratively refined regularization
107. Optimal, small kernels for edge detection
108. Advances in mathematical models for image processing
109. Image segmentation using simple Markov random field models
110. Application of the Gibbs distribution to image segmentation
111. Bayes smoothing algorithms for segmentation of binary images modeled by Markov random fields
112. Stochastic relaxation, Gibbs distribution, and the Bayesian restoration of images
113. Application of Markov Random Field models to the design and analysis of image segmentation algorithm
114. A recursive algorithm for the Bayes solution of the smoothing problem
115. Modelling and segmentation of noisy and textured images using Gibbs Random Fields
116. Image enhancement using fuzzy sets
117. Automatic grey level thresholding through index of fuzziness and entropy
118. Analysing a real world scene sequence using fuzziness
119. A quantitative index of information and a method of enhancement for digital imaging using fuzzy sets
120. Image enhancement and thresholding by optimization of fuzzy compactness
121. Fuzzy thresholding: mathematical framework, bound functions and weighted moving average technique
122. On image information measures and object extraction
123. Higher order fuzzy entropy and hybrid entropy of a set
124. Low-level segmentation of aerial images with fuzzy clustering
125. A comparison of neural network and fuzzy clustering techniques in segmenting magnetic resonance images of the brain
126. Efficient implementation of fuzzy c-means clustering algorithms
127. Image segmentation in presence of uncertainty
128. The fuzzy integral in image segmentation
129. Multispectral image segmentation using fuzzy techniques
130. Conditional fuzzy measures and image segmentation
131. Index of area coverage of fuzzy image subsets and object extraction
132. Experimentally derived fuzzy membership function for gray level images
133. Image segmentation using fuzzy correlation
134. The fuzzy geometry of image subsets
135. Spectral fuzzy sets and soft thresholding
136. Approximate reasoning for recognition in color image of beef steaks
137. Object enhancement and extraction
138. Some information measures on fuzzy sets and their applications to image processing
139. From binary to gray tone image processing using fuzzy logic concepts
140. On edge detection of X-ray images using fuzzy set
141. A note on the use of local max and min operations in digital picture processing
142. A connectionist classifier architecture applied to image segmentation
143. Connectionist model binarization
144. Stochastic and deterministic network for texture segmentation
145. Image segmentation using a neural network
146. Parameter estimation multiscale representation and algorithms for energy-minimizing segmentation
147. Self-organization for object extraction using multilayer neural networks and fuzziness measure
148. A network system for image segmentation
149. Neural network, Gibbs distribution and object extraction
150. Object extraction using a self organizing neural network
151. Medical image segmentation by a constraint satisfaction neural network
152. Object background classification using Hopfield type neural network
153. Texture segmentation using multilayered back propagation
154. On the color image segmentation algorithm based on the thresholding and fuzzy c-means techniques
155. Fuzzy sets and decision making in color image processing
156. Color information for region segmentation
157. Picture segmentation using a recursive region splitting method
158. An information measure for a color space
159. Iterative fuzzy image segmentation
160. An experimental rule based system for testing low level segmentation strategy