14.4.2 Syntactic Methods for Region Segmentation

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Segmentation. Syntactic.

Narasimhan, R.,
Labeling Schemata and Syntactic Descriptions of Pictures,
InfoControl(7), No. 2, June 1964, pp. 151-179. BibRef 6406

Narasimhan, R.,
Syntax-Directed Interpretation of Classes of Pictures,
CACM(9), 1966, pp. 166-173. BibRef 6600

Narasimhan, R.,
On the Description, Generation, and Recognition of Classes of Pictures,
AII(1-42). 1969. BibRef 6900

Reddy, V.S.N., Narasimhan, R.,
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CGIP(1), No. 4, December 1972, pp. 386-393.
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analysis of picture languages. BibRef

Clowes, M.B.,
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Baird, M.L.[Michael L.], Kelly, M.D.[Michael D.],
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Thomason, M.G., Gonzalez, R.C.,
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Thomason, M.G.,
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Fung, L.W., and Fu, K.S.,
Stochastic Syntactic Decoding for Pattern Classification,
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Maximum Likelihood Syntactic Decoding,
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Fu, K.S., Booth, T.L.,
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Majumdar, A.K., Roy, A.K.,
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Aleksander, I.,
Emergent Intelligent Properties of Progressively Structured Pattern Recognition Nets,
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Pathak, A., Pal, S.K., King, R.A.,
Syntactic Recognition of Skeletal Maturity,
PRL(2), 1984, pp. 193-197. BibRef 8400

Don, H.S.[Hon-Son], Fu, K.S.[King-Sun],
A Parallel Algorithm for Stochastic Image Segmentation,
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Don, H.S.[Hon-Son], Fu, K.S.[King-Sun],
A Syntactic Method for Image Segmentation and Object Recognition,
PR(18), No. 1, 1985, pp. 73-87.
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Earlier: ICPR84(1380-1382). Segmentation and recognition. SAR application. BibRef

Don, H.S.[Hon-Son],
Stochastic Image Segmentation Using Spatial-Temporal Context,
ICPR88(I: 342-344).
IEEE DOI BibRef 8800

Chiang, Y.T., and Fu, K.S.,
Parallel Parsing Algorithms and VLSI Implementation for Syntactic Pattern Recognition,
PAMI(6), No. 3, May 1984, pp. 302-313. BibRef 8405

Huang, K.Y.[Kou-Yuan], Fu, K.S.[King-Sun],
Syntactic Pattern Recognition for the Recognition of Bright Spots,
PR(18), No. 6, 1985, pp. 421-428.
Elsevier DOI Seismic traces. BibRef 8500

Cheng, H.D., Lin, W.C., Fu, K.S.[King-Sun],
Space-Time Domain Expansion Approach to VLSI and Its Application to Hierarchical Scene Matching,
PAMI(7), No. 3, May 1985, pp. 306-319. BibRef 8505
Earlier: ICPR84(578-580). BibRef

Basu, S., Fu, K.S.,
Image Segmentation By Syntactic Method,
PR(20), No. 1, 1987, pp. 33-44.
Elsevier DOI Edges, curves, corners. BibRef 8700

Basu, S.,
Image Segmentation By Semantic Method,
PR(20), No. 5, 1987, pp. 497-511.
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Basu, S.,
On the relationship between augmented transition network and attributed grammar,
ICPR88(I: 337-341).

Straub, B.J., Blanz, W.E.,
Combined Decision Theoretic and Syntactic Approach to Image Segmentation,
MVA(2), 1989, pp. 17-30. BibRef 8900

Huang, T.S., and Fu, K.S.,
Image Segmentation by a Syntactic Method,
PurdueTR-16, March 1977. Texture regions (co-occurrence matrix); boundaries (?); 1 min (360-67) for 88x88 image. BibRef 7703

Janmin, K.[Kang],
Syntactic Algorithms for Image Segmentation and a Special Computer Architecture for Image Processing,
PurdueTR-77-39, December 1977. Syntactic: structural or spatial analysis rather than statistical, and a grammar is inferred to describe structures of patterns in an image. Syntax directed: syntactic analysis is performed by a template matching which is directed by the syntactic rules. Syntax controlled: an automaton (e.g., a parser, deterministic F.S.M.) (??) which is directly controlled by the syntactic rules is used for the syntactic analysis. Tree grammar; structural properties of subpatterns (size, shape arrangement). BibRef 7712

Shi, Q.Y., and Fu, K.S.,
Parsing and Translation of (Attributed) Expansive Graph Languages for Scene Analysis,
PAMI(5), No. 5, September 1983, pp. 472-485. BibRef 8309

Shi, Q.Y., and Fu, K.S.,
A Method for the Design of Binary Tree Classifiers,
PR(16), No. 6, 1983, pp. 593-603.
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Lucas, S., Amiri, A.,
Statistical Syntactic Methods for High-Performance OCR,
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Sinha, R.M.K.,
PLANG: A Picture Language Schema for a Class of Pictures,
PR(16), No. 4, 1983, pp. 373-383.
Elsevier DOI 9611
curvilinear elements. BibRef

Mohr, R.[Roger],
Precompilation of Syntactical Descriptions and Knowledge Directed Analysis of Patterns,
PR(19), No. 4, 1986, pp. 255-266.
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Henderson, T.C.[Thomas C.], Samal, A.[Ashok],
Shape Grammar Compilers,
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Bengtsson, M.,
Stochastic Optimization Algorithms: An Application to Pattern Matching,
PRL(11), 1990, pp. 717-724. BibRef 9000

Biswas, G., Dubes, R.C.,
Some Experiments in Two-Dimensional Grammatical Inference,
PRL(2), 1984, pp. 173-177. BibRef 8400

Araujo, C.P.S.,
Novel Neural-Network Models for Computing Homothetic Invariances: An Image Algebra Notation,
JMIV(7), No. 1, January 1997, pp. 69-83.
DOI Link 9703

Sanfeliu, A.,
TC2: Structural and Syntactic Pattern-Recognition: Aims, Scope, History and Activities,
PRL(18), No. 4, April 1997, pp. 403-406. 9708

Wang, W., Pollak, I., Wong, T.S., Bouman, C.A., Harper, M.P., Siskind, J.M.,
Hierarchical Stochastic Image Grammars for Classification and Segmentation,
IP(15), No. 10, October 2006, pp. 3033-3052.

Zhu, S.C.[Song-Chun], Mumford, D.[David],
A Stochastic Grammar of Images,
World ScientificSingapore, 2007. ISBN: 978-1-60198-060-1. BibRef 0700

Siddiqi, K.[Kaleem], Kimia, B.B.[Benjamin B.],
A Shock Grammar for Recognition,
IEEE DOI MAT. BibRef 9600

Truve, S.,
Image Interpretation Using Multi-Relational Grammars,
IEEE DOI BibRef 9000

Sanfeliu, A., Serratosa, F.,
Learning and recognising 3d models represented by multiple views by means of methods based on random graphs,
ICIP03(II: 29-32).

Sanfeliu, A., Sainz, M.,
Learning Bidimensional Context Dependent Models Using a Context Sensitive Language,
ICPR96(IV: 565-569).
(Univ. Politecnica de Catalunya, E) BibRef

Fred, A.L.N., Leitao, J.M.N.,
A Minimum Code Length Technique for Clustering of Syntactic Patterns,
ICPR96(II: 680-684).
(Instituto de Telecomunicacoes, P) BibRef

Fred, A.L.N., Leitao, J.M.N.,
Solomonoff coding as a means of introducing prior information in syntactic pattern recognition,
Use of stochastic grammars for hypnogram analysis,

Keng, J.,
Syntactic algorithms for image segmentation and a special computer architecture for image processing,
Ph.D.Thesis, December 1977. Purdue University, West Lafayette, IN. BibRef 7712

Chapter on Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms continues in
Decision Trees .

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