| 1. Identity statement | ||||
| Reference Type | Conference Paper (Conference Proceedings) | |||
| Site | sibgrapi.sid.inpe.br | |||
| Holder Code | ibi 8JMKD3MGPEW34M/46T9EHH | |||
| Identifier | 8JMKD3MGPEW34M/45CU3E2 | |||
| Repository | sid.inpe.br/sibgrapi/2021/09.06.17.42 | |||
| Last Update | 2021:09.06.17.46.22 (UTC) administrator | |||
| Metadata Repository | sid.inpe.br/sibgrapi/2021/09.06.17.42.05 | |||
| Metadata Last Update | 2022:07.30.04.21.05 (UTC) administrator | |||
| DOI | 10.1109/SIBGRAPI54419.2021.00053 | |||
| Citation Key | AlmeidaPaArKiMaGu:2021:DeImGr | |||
| Title | Descriptive Image Gradient from Edge-Weighted Image Graph and Random Forests  | |||
| Format | On-line | |||
| Year | 2021 | |||
| Access Date | 2024, May 06 | |||
| Number of Files | 1 | |||
| Size | 2598 KiB | |||
| 2. Context | ||||
| Author | 1 Almeida, Raquel 2 Patrocínio Junior, Zenilton K. G. 3 Araújo, Arnaldo de Albuquerque 4 Kijak, Ewa 5 Malinowski, Simon 6 Guimarães, Silvio Jamil F. | |||
| Affiliation | 1 PUC Minas and Université de Rennes 1, Brazil and France 2 PUC Minas, Belo Horizonte, Brazil 3 Universidade Federal de Minas Gerais, Belo Horizonte, Brazil 4 Université de Rennes 1, Rennes, France 5 Université de Rennes 1, Rennes, France 6 PUC Minas, Belo Horizonte, Brazil | |||
| Editor | Paiva, Afonso Menotti, David Baranoski, Gladimir V. G. Proença, Hugo Pedro Junior, Antonio Lopes Apolinario Papa, João Paulo Pagliosa, Paulo dos Santos, Thiago Oliveira e Sá, Asla Medeiros da Silveira, Thiago Lopes Trugillo Brazil, Emilio Vital Ponti, Moacir A. Fernandes, Leandro A. F. Avila, Sandra | |||
| e-Mail Address | raquel1908@gmail.com | |||
| Conference Name | Conference on Graphics, Patterns and Images, 34 (SIBGRAPI) | |||
| Conference Location | Gramado, RS, Brazil (virtual) | |||
| Date | 18-22 Oct. 2021 | |||
| Publisher | IEEE Computer Society | |||
| Publisher City | Los Alamitos | |||
| Book Title | Proceedings | |||
| Tertiary Type | Full Paper | |||
| History (UTC) | 2021-09-06 17:46:23 :: raquel1908@gmail.com -> administrator :: 2021 2022-03-02 00:54:15 :: administrator -> menottid@gmail.com :: 2021 2022-03-02 13:15:06 :: menottid@gmail.com -> administrator :: 2021 2022-07-30 04:21:05 :: administrator -> :: 2021 | |||
| 3. Content and structure | ||||
| Is the master or a copy? | is the master | |||
| Content Stage | completed | |||
| Transferable | 1 | |||
| Version Type | finaldraft | |||
| Keywords | Image gradient Random forest graph segmentation | |||
| Abstract | Creating an image gradient is a transformation process that aims to enhance desirable properties of an image, whilst leaving aside noise and non-descriptive characteristics. Many algorithms in image processing rely on a good image gradient to perform properly on tasks such as edge detection and segmentation. In this work, we propose a novel method to create a very descriptive image gradient using edge-weighted graphs as a structured input for the random forest algorithm. On the one side, the spatial connectivity of the image pixels gives us a structured representation of a grid graph, creating a particular transformed space close to the spatial domain of the images, but strengthened with relational aspects. On the other side, random forest is a fast, simple and scalable machine learning method, suited to work with high-dimensional and small samples of data. The local variation representation of the edge-weighted graph, aggregated with the random forest implicit regularization process, serves as a gradient operator delimited by the graph adjacency relation in which noises are mitigated and desirable characteristics reinforced. In this work, we discuss the graph structure, machine learning on graphs and the random forest operating on graphs for image processing. We tested the created gradients on the hierarchical watershed algorithm, a segmentation method that is dependent on the input gradient. The segmentation results obtained from the proposed method demonstrated to be superior compared to other popular gradients methods. | |||
| Arrangement 1 | urlib.net > SDLA > Fonds > SIBGRAPI 2021 > Descriptive Image Gradient... | |||
| Arrangement 2 | urlib.net > SDLA > Fonds > Full Index > Descriptive Image Gradient... | |||
| doc Directory Content | access | |||
| source Directory Content | there are no files | |||
| agreement Directory Content |
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| 4. Conditions of access and use | ||||
| data URL | http://urlib.net/ibi/8JMKD3MGPEW34M/45CU3E2 | |||
| zipped data URL | http://urlib.net/zip/8JMKD3MGPEW34M/45CU3E2 | |||
| Language | en | |||
| Target File | PaperID31.pdf | |||
| User Group | raquel1908@gmail.com | |||
| Visibility | shown | |||
| Update Permission | not transferred | |||
| 5. Allied materials | ||||
| Mirror Repository | sid.inpe.br/banon/2001/03.30.15.38.24 | |||
| Next Higher Units | 8JMKD3MGPEW34M/45PQ3RS 8JMKD3MGPEW34M/4742MCS | |||
| Citing Item List | sid.inpe.br/sibgrapi/2021/11.12.11.46 5 | |||
| Host Collection | sid.inpe.br/banon/2001/03.30.15.38 | |||
| 6. Notes | ||||
| Empty Fields | archivingpolicy archivist area callnumber contenttype copyholder copyright creatorhistory descriptionlevel dissemination edition electronicmailaddress group isbn issn label lineage mark nextedition notes numberofvolumes orcid organization pages parameterlist parentrepositories previousedition previouslowerunit progress project readergroup readpermission resumeid rightsholder schedulinginformation secondarydate secondarykey secondarymark secondarytype serieseditor session shorttitle sponsor subject tertiarymark type url volume | |||