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Development and assessment of novel and accurate methods in shape analysis and computer vision


Before image processing and vision techniques can be effectively applied in a truly comprehensive fashion, the involved techniques and implementations have to reach high performance standards. A particularly promising possibility for achieving such a relevant and challenging objective consists in comprehensive and integrated approaches to the typical related problems, including shape representation and its use as subsidy for visual analysis, classification, and synthesis. The inherent advantage in such approaches is that the specific demands and qualities of the processes at each subsequent stage (for instance representation and classification) can be properly identified and complemented. At the same time, it becomes essential to devise and apply formal performance validation and comparative assessment procedures, capable of properly characterizing the potential and short comings of the considered and developed techniques. The current project can be divided into the following two principal parts: (a) development and validation of new representations of visual information,(particularly shapes) and their respective use in analysis, classification and synthesis of 2D, 2.5D and 3D shapes, with special emphasis on scale-space approaches based on differential geometry, partial differential equations, signal processing, and skeletonization; and (b) developments and applications in the areas of tunelling microscopy (2.5D images), face recognition, and industrial parts identification. Additional research topics also to be considered in the planned developments include techniques for multiscale image processing and analysis (such as wavelets and mathematical morphology), digital video processing and motion analysis. (AU)

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Scientific publications (29)
(References retrieved automatically from Web of Science and SciELO through information on FAPESP grants and their corresponding numbers as mentioned in the publications by the authors)
COSTA, L. DA F.; COUPEZ, V.; BARBOSA, M. S.. A direct approach to neuronal connectivity. PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS, v. 341, n. 1-2, p. 618-628, . (02/02504-1, 99/12765-2)
COSTA, L. DA F.; BARBOSA, M. S.. An analytical approach to neuronal connectivity. European Physical Journal B, v. 42, n. 4, p. 573-580, . (99/12765-2)
DA F COSTA‚ L.; RODRIGUES‚ F.A.; TRAVIESO‚ G.. Protein domain connectivity and essentiality. Applied Physics Letters, v. 89, n. 17, p. 174101-174101, . (99/12765-2)
VIANA, MATHEUS PALHARES; TANCK, ESTHER; BELETTI, MARCELO EMILIO; COSTA, LUCIANO DA FONTOURA. Modularity and robustness of bone networks. MOLECULAR BIOSYSTEMS, v. 5, n. 3, p. 255-261, . (05/00587-5, 07/50882-9, 99/12765-2)
GONCALVES, WESLEY NUNES; DA SILVA, NUBIA ROSA; COSTA, LUCIANO DA FONTOURA; BRUNO, ODEMIR MARTINEZ. Texture recognition based on diffusion in networks. INFORMATION SCIENCES, v. 364, p. 51-71, . (11/21467-9, 10/08614-0, 05/00587-5, 11/01523-1, 99/12765-2)
DA F COSTA‚ L.; DOS REIS‚ S.F.; ARANTES‚ R.A.T.; ALVES‚ A.C.R.; MUTINARI‚ G.C.. Biological shape analysis by digital curvature. PATTERN RECOGNITION, v. 37, n. 3, p. 515-524, . (99/12765-2)
DA FONTOURA COSTA‚ L.. Reinforcing the resilience of complex networks. Physical Review E, v. 69, n. 6, p. 066127, . (99/12765-2)
COSTA‚ L.F.. Estimating derivatives and curvature of open curves. PATTERN RECOGNITION, v. 35, n. 11, p. 2445-2451, . (99/12765-2)
BELETTI‚ ME; COSTA‚ L.F.; VIANA‚ MP. A computational approach to characterization of bovine sperm chromatin alterations. BIOTECHNIC & HISTOCHEMISTRY, v. 79, n. 1, p. 17-23, . (99/12765-2)
DA S TORRES‚ R.; FALCAO‚ AX; DA F COSTA‚ L.. A graph-based approach for multiscale shape analysis. PATTERN RECOGNITION, v. 37, n. 6, p. 1163-1174, . (99/12765-2)
CESAR‚ R.M.; BENGOETXEA‚ E.; BLOCH‚ I.; LARRAÑAGA‚ P.. Inexact graph matching for model-based recognition: Evaluation and comparison of optimization algorithms. PATTERN RECOGNITION, v. 38, n. 11, p. 2099-2113, . (99/12765-2)
DIAMBRA‚ L.; COSTA‚ L.F.. Complex networks approach to gene expression driven phenotype imaging. Bioinformatics, v. 21, n. 20, p. 3846-3851, . (99/12765-2)
BARBOSA‚ M.S.; DA FONTOURA COSTA‚ L.; DE SOUSA BERNARDES‚ E.. Neuromorphometric characterization with shape functionals. Physical Review E, v. 67, n. 6, p. 061910, . (99/12765-2)
DA FONTOURA COSTA‚ L.. L-percolations of complex networks. Physical Review E, v. 70, n. 5, p. 056106, . (99/12765-2)
COSTA‚ L.F.; CINTRA‚ L.C.; SCHUBERT‚ D.. An integrated approach to the characterization of cell movement. Cytometry Part A, v. 68, n. 2, p. 92-100, . (99/12765-2)
DA FONTOURA COSTA‚ L.; ROCHA‚ F.; DE LIMA‚ S.M.A.. Characterizing polygonality in biological structures. Physical Review E, v. 73, n. 1, p. 011913, . (99/12765-2)
CAMPITELI, MONICA GUIMARAES; COMIN, CESAR HENRIQUE; COSTA, LUCIANO DA FONTOURA; BABU, M. MADAN; CESAR, JR., ROBERTO MARCONDES. A methodology to infer gene networks from spatial patterns of expression - an application to fluorescence in situ hybridization images. MOLECULAR BIOSYSTEMS, v. 9, n. 7, p. 1926-1930, . (11/22639-8, 05/00587-5, 99/12765-2)
COSTA, L. DA F.; BARBOSA, M. S.; MANOEL, E. T. M.; STREICHER, J.; MÜLLER, G. B.. Mathematical characterization of three-dimensional gene expression patterns. Bioinformatics, v. 20, n. 11, p. 1653-1662, . (02/02504-1, 99/12765-2)
DA FONTOURA COSTA‚ L.; ROCHA‚ F.; ARAÚJO DE LIMA‚ S.M.. Statistical mechanics characterization of neuronal mosaics. Applied Physics Letters, v. 86, n. 9, p. 093901-093901, . (99/12765-2)
CAMPOS BIANCHI‚ A.G.; DOS SANTOS‚ M.F.; HAMASSAKI BRITTO‚ D.E.; COSTA‚ L.F.. Inferring shape evolution. PATTERN RECOGNITION LETTERS, v. 24, n. 7, p. 1005-1014, . (01/09047-2, 99/12765-2)
COSTA‚ L.F.. The hierarchical backbone of complex networks. Physical Review Letters, v. 93, n. 9, p. 98702, . (99/12765-2)
DA FONTOURA COSTA‚ L.; VIANA‚ M.P.; BELETTI‚ M.E.. Complex channel networks of bone structure. Applied Physics Letters, v. 88, p. 033903, . (99/12765-2)
RODRIGUES‚ E.P.; BARBOSA‚ M.S.; COSTA‚ L.F.. Self-referred approach to lacunarity. Physical Review E, v. 72, n. 1, p. 016707, . (99/12765-2, 02/02504-1)
DA FONTOURA COSTA‚ L.; DIAMBRA‚ L.. Topographical maps as complex networks. Physical Review E, v. 71, n. 2, p. 021901, . (99/12765-2)
DA FONTOURA COSTA‚ L.; MANOEL‚ E.T.M.. A percolation approach to neural morphometry and connectivity. NEUROINFORMATICS, v. 1, n. 1, p. 65-80, . (99/12765-2)
DIAMBRA‚ L.; DA FONTOURA COSTA‚ L.. Pattern formation in a gene network model with boundary shape dependence. Physical Review E, v. 73, n. 3, p. 031917, . (99/12765-2)
DA FONTOURA COSTA‚ L.. Biological sequence analysis through the one-dimensional percolation transform and its enhanced version. Bioinformatics, v. 21, n. 5, p. 608-616, . (99/12765-2)
DA FONTOURA COSTA‚ L.. Learning about knowledge: A complex network approach. Physical Review E, v. 74, n. 2, p. 026103, . (99/12765-2)

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