Development of robust methods for edge delineation in images using graphs

• Grant number: 16/21591-5
• Support Opportunities: Regular Research Grants
• Start date: August 01, 2017
• End date: July 31, 2019
• Field of knowledge: Physical Sciences and Mathematics - Computer Science - Computing Methodologies and Techniques
• Principal Investigator: Fábio Augusto Menocci Cappabianco
• Grantee: Fábio Augusto Menocci Cappabianco
• Host Institution: Instituto de Ciência e Tecnologia (ICT). Universidade Federal de São Paulo (UNIFESP). Campus São José dos Campos. São José dos Campos , SP, Brazil
• Associated researchers: Alexandre Xavier Falcão ; Clarissa Lin Yasuda ; Fabio Augusto Faria ; Jaime Shinsuke Ide ; Jurandy Gomes de Almeida Junior ; Marcos de Sales Guerra Tsuzuki ; Paulo André Vechiatto de Miranda

Abstract

Delineating the edges of objects in images is important in the context of several knowledge areas, including medicine and remote sensing. The segmentation of organs and tissues of the human brain, for instance, is a necessary step in the study of the etiology, diagnosis, and treatment of diseases such as Alzheimer's and schizophrenia. Also, the classification of types of terrains helps preventing deforestation and measuring water levels enables issuing flood or drought alerts. Nevertheless, existing automatic and semi-automatic tools for borders delineation still suffers major flaws in dealing with discontinuities, noise, color, intensity, and texture variation. This project aims at studying alternatives to the current border delineation methodologies using graphs being: live-wire, riverbed and lazy walk. We will study mechanisms to enhance the interaction of the user in semi-automated tools for bi- and tri-dimensional delineation, the choice of functions for edge weight generation, the selection of path propagation functions in graphs, and supervised learning techniques so that the most relevant edges are identified with less effort and accuracy for each specific application. (AU)

Scientific publications

(16)

(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)

BEJAR, HANS H. C.; FERZOLI GUIMARAES, SILVIO JAMIL; MIRANDA, V, PAULO A.. Efficient hierarchical graph partitioning for image segmentation by optimum oriented cuts. PATTERN RECOGNITION LETTERS, v. 131, p. 185-192, MAR 2020. (14/12236-1, 16/21591-5)

ANDRADE, NATAN; FARIA, FABIO A.; CAPPABIANCO, FABIO A. M.; IEEE COMP SOC. Improving Similarity Metric of Multi-modal MR Brain Image Registration Via a Deep Ensemble. 2021 34TH SIBGRAPI CONFERENCE ON GRAPHICS, PATTERNS AND IMAGES (SIBGRAPI 2021), v. N/A, p. 8-pg., 2021-01-01. (18/23908-1, 16/21591-5)

BRAZ, CAIO DE MORAES; MIRANDA, PAULO A., V; CIESIELSKI, KRZYSZTOF CHRIS; CAPPABIANCO, FABIO A. M.; COUPRIE, M; COUSTY, J; KENMOCHI, Y; MUSTAFA, N. Graph-Based Segmentation with Local Band Constraints. DISCRETE GEOMETRY FOR COMPUTER IMAGERY, DGCI 2019, v. 11414, p. 12-pg., 2019-01-01. (14/12236-1, 16/21591-5)

CAPPABIANCO, FABIO A. M.; RIBEIRO, PEDRO F. O.; DE MIRANDA, PAULO A. V.; UDUPA, JAYARAM K.; IEEE. A GENERAL AND BALANCED REGION-BASED METRIC FOR EVALUATING MEDICAL IMAGE SEGMENTATION ALGORITHMS. 2019 IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING (ICIP), v. N/A, p. 5-pg., 2019-01-01. (16/21591-5)

DEMARIO, CAIO L.; MIRANDA, PAULO A. V.; IEEE. RELAXED ORIENTED IMAGE FORESTING TRANSFORM FOR SEEDED IMAGE SEGMENTATION. 2019 IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING (ICIP), v. N/A, p. 5-pg., 2019-01-01. (14/12236-1, 16/21591-5)

CONDORI, MARCOS A. T.; CAPPABIANCO, FABIO A. M.; FALCAO, ALEXANDRE X.; MIRANDA, PAULO A., V. An extension of the differential image foresting transform and its application to superpixel generation. JOURNAL OF VISUAL COMMUNICATION AND IMAGE REPRESENTATION, v. 71, p. 15-pg., 2020-08-01. (16/21591-5, 14/12236-1, 11/50761-2, 14/50937-1)

CAPPABIANCO, FABIO A. M.; DE MIRANDA, PAULO A. V.; UDUPA, JAYARAM K.; IEEE. A CRITICAL ANALYSIS OF THE METHODS OF EVALUATING MRI BRAIN SEGMENTATION ALGORITHMS. 2017 24TH IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING (ICIP), v. N/A, p. 5-pg., 2017-01-01. (16/21591-5)

BRAZ, CAIO DE MORAES; MIRANDA, PAULO A. V.; CIESIELSKI, KRZYSZTOF CHRIS; CAPPABIANCO, FABIO A. M.. Optimum Cuts in Graphs by General Fuzzy Connectedness with Local Band Constraints. Journal of Mathematical Imaging and Vision, v. 62, n. 5, SI, MAR 2020. (14/12236-1, 16/21591-5)

BRAGANTINI, JORDAO; MOURA, BRUNO; FALCAO, ALEXANDRE X.; CAPPABIANCO, FABIO A. M.. Grabber: A tool to improve convergence in interactive image segmentation. PATTERN RECOGNITION LETTERS, v. 140, p. 267-273, DEC 2020. (14/12236-1, 19/11349-0, 16/21591-5)

IDE, JAIME S.; CAPPABIANCO, FABIO A.; FARIA, FABIO A.; LI, CHIANG-SHAN R.; GUYON, I; LUXBURG, UV; BENGIO, S; WALLACH, H; FERGUS, R; VISHWANATHAN, S; et al. Detrended Partial Cross Correlation for Brain Connectivity Analysis. ADVANCES IN NEURAL INFORMATION PROCESSING SYSTEMS 30 (NIPS 2017), v. 30, p. 9-pg., 2017-01-01. (16/21591-5)

CASTANEDA LEON, LEISSI M.; MIRANDA, PAULO A. V.; IEEE. Multi-Object Segmentation by Hierarchical Layered Oriented Image Foresting Transform. 2017 30TH SIBGRAPI CONFERENCE ON GRAPHICS, PATTERNS AND IMAGES (SIBGRAPI), v. N/A, p. 8-pg., 2017-01-01. (14/50937-1, 16/21591-5, 11/50761-2)

BRAZ, CAIO DE MORAES; MIRANDA, PAULO A. V.; CIESIELSKI, KRZYSZTOF CHRIS; CAPPABIANCO, FABIO A. M.. Optimum Cuts in Graphs by General Fuzzy Connectedness with Local Band Constraints. Journal of Mathematical Imaging and Vision, v. 62, n. 5, p. 14-pg., 2020-03-27. (14/12236-1, 16/21591-5)

BEJAR, HANS H. C.; CAPPABIANCO, FABIO A. M.; MIRANDA, PAULO A. V.; BATTIATO, S; GALLO, G; SCHETTINI, R; STANCO, F. Efficient Image Segmentation in Graphs with Localized Curvilinear Features. IMAGE ANALYSIS AND PROCESSING,(ICIAP 2017), PT I, v. 10484, p. 11-pg., 2017-01-01. (16/21591-5, 11/50761-2, 14/12236-1)

CONDORI, MARCOS A. T.; CAPPABIANCO, FABIO A. M.; FALCAO, ALEXANDRE X.; MIRANDA, PAULO A. V.; IEEE. Extending the Differential Image Foresting Transform to Root-based Path-cost Functions with Application to Superpixel Segmentation. 2017 30TH SIBGRAPI CONFERENCE ON GRAPHICS, PATTERNS AND IMAGES (SIBGRAPI), v. N/A, p. 8-pg., 2017-01-01. (16/21591-5, 11/50761-2)

CAPPABIANCO, FABIO A. M.; DOS SANTOS, SERGIO R. B.; IDE, JAIME S.; DA SILVA, PETRUS P. C. E.; IEEE. NON-LOCAL OPERATIONAL ANISOTROPIC DIFFUSION FILTER. 2019 IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING (ICIP), v. N/A, p. 5-pg., 2019-01-01. (16/21591-5)

YASUDA, YURI D., V; MARTINS, LUIZ EDUARDO G.; CAPPABIANCO, FABIO A. M.. Autonomous Visual Navigation for Mobile Robots: A Systematic Literature Review. ACM COMPUTING SURVEYS, v. 53, n. 1, p. 34-pg., 2020-02-01. (16/21591-5)