| Full text | |
| Author(s): |
Total Authors: 3
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| Affiliation: | [1] V, Univ Sao Paulo, Inst Math & Stat, Dept Comp Sci, Rua Matao 1010, BR-05508090 Sao Paulo, SP - Brazil
[2] Pontificia Univ Catolica Minas Gerais, Comp Sci Dept, Rua Walter Ianni 255, BR-31980110 Belo Horizonte, MG - Brazil
Total Affiliations: 2
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| Document type: | Journal article |
| Source: | PATTERN RECOGNITION LETTERS; v. 131, p. 185-192, MAR 2020. |
| Web of Science Citations: | 0 |
| Abstract | |
In this work, a hierarchical graph partitioning based on optimum cuts in graphs is proposed for unsupervised image segmentation, that can be tailored to the target group of objects, according to their boundary polarity, by extending Oriented Image Foresting Transform (OIFT). The proposed method, named UOIFT, theoretically encompasses as a particular case the single-linkage algorithm by minimum spanning tree (MST) and gives superior segmentation results compared to other approaches commonly used in the literature, usually requiring a lower number of image partitions to accurately isolate the desired regions of interest with known polarity. The method is supported by new theoretical results involving the usage of non-monotonic-incremental cost functions in directed graphs and exploits the local contrast of image regions, being robust in relation to illumination variations and inhomogeneity effects. UOIFT is demonstrated using a region adjacency graph of superpixels in medical and natural images. (c) 2020 Elsevier B.V. All rights reserved. (AU) | |
| FAPESP's process: | 14/12236-1 - AnImaLS: Annotation of Images in Large Scale: what can machines and specialists learn from interaction? |
| Grantee: | Alexandre Xavier Falcão |
| Support Opportunities: | Research Projects - Thematic Grants |
| FAPESP's process: | 16/21591-5 - Development of robust methods for edge delineation in images using graphs |
| Grantee: | Fábio Augusto Menocci Cappabianco |
| Support Opportunities: | Regular Research Grants |