Publicação
A feasibility cachaca type recognition using computer vision and pattern recognition
| Resumo: | Brazilian rum (also known as cachaça) is the third most commonly consumed distilled alcoholic drink in the world, with approximately 2.5 billion liters produced each year. It is a traditional drink with refined features and a delicate aroma that is produced mainly in Brazil but consumed in many countries. It can be aged in various types of wood for 1-3 years, which adds aroma and a distinctive flavor with different characteristics that affect the price. A research challenge is to develop a cheap automatic recognition system that inspects the finished product for the wood type and the aging time of its production. Some classical methods use chemical analysis, but this approach requires relatively expensive laboratory equipment. By contrast, the system proposed in this paper captures image signals from samples and uses an intelligent classification technique to recognize the wood type and the aging time. The classification system uses an ensemble of classifiers obtained from different wavelet decompositions. Each classifier is obtained with different wavelet transform settings. We compared the proposed approach with classical methods based on chemical features. We analyzed 105 samples that had been aged for 3 years and we showed that the proposed solution could automatically recognize wood types and the aging time with an accuracy up to 100.00% and 85.71% respectively, and our method is also cheaper. |
|---|---|
| Autores principais: | Rodrigues, Bruno Urbano |
| Outros Autores: | Soares, Anderson da Silva; Costa, Ronaldo Martins da; Van Baalen, J.; Salvini, Rogério Lopes; Silva, Flávio Alves da; Caliari, Márcio; Cardoso, Karla Cristina Rodrigues; Ribeiro, Tânia Isabel Monteiro; Delbem, A.C.B.; Federson, F.M.; Coelho, C.J.; Laureano, G.T.; Lima, T.W. |
| Assunto: | Computer vision Drinks Pattern recognition |
| Ano: | 2016 |
| País: | Portugal |
| Tipo de documento: | artigo |
| Tipo de acesso: | acesso aberto |
| Instituição associada: | Instituto Politécnico de Bragança |
| Idioma: | inglês |
| Origem: | Biblioteca Digital do IPB |
| _version_ | 1867173344973946880 |
|---|---|
| author | Rodrigues, Bruno Urbano |
| author2 | Soares, Anderson da Silva Costa, Ronaldo Martins da Van Baalen, J. Salvini, Rogério Lopes Silva, Flávio Alves da Caliari, Márcio Cardoso, Karla Cristina Rodrigues Ribeiro, Tânia Isabel Monteiro Delbem, A.C.B. Federson, F.M. Coelho, C.J. Laureano, G.T. Lima, T.W. |
| author2_role | author author author author author author author author author author author author author |
| author_facet | Rodrigues, Bruno Urbano Soares, Anderson da Silva Costa, Ronaldo Martins da Van Baalen, J. Salvini, Rogério Lopes Silva, Flávio Alves da Caliari, Márcio Cardoso, Karla Cristina Rodrigues Ribeiro, Tânia Isabel Monteiro Delbem, A.C.B. Federson, F.M. Coelho, C.J. Laureano, G.T. Lima, T.W. |
| author_role | author |
| contributor_name_str_mv | Biblioteca Digital do IPB |
| country_str | PT |
| creators_json_txt | [{\"Person.name\":\"Rodrigues, Bruno Urbano\"},{\"Person.name\":\"Soares, Anderson da Silva\"},{\"Person.name\":\"Costa, Ronaldo Martins da\"},{\"Person.name\":\"Van Baalen, J.\"},{\"Person.name\":\"Salvini, Rogério Lopes\"},{\"Person.name\":\"Silva, Flávio Alves da\"},{\"Person.name\":\"Caliari, Márcio\"},{\"Person.name\":\"Cardoso, Karla Cristina Rodrigues\"},{\"Person.name\":\"Ribeiro, Tânia Isabel Monteiro\"},{\"Person.name\":\"Delbem, A.C.B.\"},{\"Person.name\":\"Federson, F.M.\"},{\"Person.name\":\"Coelho, C.J.\"},{\"Person.name\":\"Laureano, G.T.\"},{\"Person.name\":\"Lima, T.W.\"}] |
| datacite.contributors.contributor.contributorName.fl_str_mv | Biblioteca Digital do IPB |
| datacite.creators.creator.creatorName.fl_str_mv | Rodrigues, Bruno Urbano Soares, Anderson da Silva Costa, Ronaldo Martins da Van Baalen, J. Salvini, Rogério Lopes Silva, Flávio Alves da Caliari, Márcio Cardoso, Karla Cristina Rodrigues Ribeiro, Tânia Isabel Monteiro Delbem, A.C.B. Federson, F.M. Coelho, C.J. Laureano, G.T. Lima, T.W. |
| datacite.date.Accepted.fl_str_mv | 2016-01-01T00:00:00Z |
| datacite.date.available.fl_str_mv | 2018-01-25T10:00:00Z |
| datacite.date.embargoed.fl_str_mv | 2018-01-25T10:00:00Z |
| datacite.rights.fl_str_mv | http://purl.org/coar/access_right/c_abf2 |
| datacite.subjects.subject.fl_str_mv | Computer vision Drinks Pattern recognition |
| datacite.titles.title.fl_str_mv | A feasibility cachaca type recognition using computer vision and pattern recognition |
| dc.contributor.none.fl_str_mv | Biblioteca Digital do IPB |
| dc.creator.none.fl_str_mv | Rodrigues, Bruno Urbano Soares, Anderson da Silva Costa, Ronaldo Martins da Van Baalen, J. Salvini, Rogério Lopes Silva, Flávio Alves da Caliari, Márcio Cardoso, Karla Cristina Rodrigues Ribeiro, Tânia Isabel Monteiro Delbem, A.C.B. Federson, F.M. Coelho, C.J. Laureano, G.T. Lima, T.W. |
| dc.date.Accepted.fl_str_mv | 2016-01-01T00:00:00Z |
| dc.date.available.fl_str_mv | 2018-01-25T10:00:00Z |
| dc.date.embargoed.fl_str_mv | 2018-01-25T10:00:00Z |
| dc.format.none.fl_str_mv | application/pdf |
| dc.identifier.none.fl_str_mv | http://hdl.handle.net/10198/15503 |
| dc.language.none.fl_str_mv | eng |
| dc.rights.none.fl_str_mv | http://purl.org/coar/access_right/c_abf2 |
| dc.subject.none.fl_str_mv | Computer vision Drinks Pattern recognition |
| dc.title.fl_str_mv | A feasibility cachaca type recognition using computer vision and pattern recognition |
| dc.type.none.fl_str_mv | http://purl.org/coar/resource_type/c_6501 |
| description | Brazilian rum (also known as cachaça) is the third most commonly consumed distilled alcoholic drink in the world, with approximately 2.5 billion liters produced each year. It is a traditional drink with refined features and a delicate aroma that is produced mainly in Brazil but consumed in many countries. It can be aged in various types of wood for 1-3 years, which adds aroma and a distinctive flavor with different characteristics that affect the price. A research challenge is to develop a cheap automatic recognition system that inspects the finished product for the wood type and the aging time of its production. Some classical methods use chemical analysis, but this approach requires relatively expensive laboratory equipment. By contrast, the system proposed in this paper captures image signals from samples and uses an intelligent classification technique to recognize the wood type and the aging time. The classification system uses an ensemble of classifiers obtained from different wavelet decompositions. Each classifier is obtained with different wavelet transform settings. We compared the proposed approach with classical methods based on chemical features. We analyzed 105 samples that had been aged for 3 years and we showed that the proposed solution could automatically recognize wood types and the aging time with an accuracy up to 100.00% and 85.71% respectively, and our method is also cheaper. |
| dirty | 0 |
| eu_rights_str_mv | openAccess |
| format | article |
| fulltext.url.fl_str_mv | https://bibliotecadigital.ipb.pt/bitstreams/4546bea5-5ae9-480d-a333-1963a3ae0981/download |
| id | ipb_458ca5ac3df9cd8ea3ad532d508c6cb8 |
| identifier.url.fl_str_mv | http://hdl.handle.net/10198/15503 |
| instacron_str | ipb |
| institution | Instituto Politécnico de Bragança |
| instname_str | Instituto Politécnico de Bragança |
| language | eng |
| network_acronym_str | ipb |
| network_name_str | Biblioteca Digital do IPB |
| oai_identifier_str | oai:bibliotecadigital.ipb.pt:10198/15503 |
| organization_str_mv | urn:organizationAcronym:ipb |
| person_str_mv | Rodrigues, Bruno Urbano Soares, Anderson da Silva Costa, Ronaldo Martins da Van Baalen, J. Salvini, Rogério Lopes Silva, Flávio Alves da Caliari, Márcio Cardoso, Karla Cristina Rodrigues Ribeiro, Tânia Isabel Monteiro Delbem, A.C.B. Federson, F.M. Coelho, C.J. Laureano, G.T. Lima, T.W. |
| publishDate | 2016 |
| reponame_str | Biblioteca Digital do IPB |
| repository_id_str | urn:repositoryAcronym:ipb |
| service_str_mv | urn:repositoryAcronym:ipb |
| spelling | engen_ENBrazilian rum (also known as cachaça) is the third most commonly consumed distilled alcoholic drink in the world, with approximately 2.5 billion liters produced each year. It is a traditional drink with refined features and a delicate aroma that is produced mainly in Brazil but consumed in many countries. It can be aged in various types of wood for 1-3 years, which adds aroma and a distinctive flavor with different characteristics that affect the price. A research challenge is to develop a cheap automatic recognition system that inspects the finished product for the wood type and the aging time of its production. Some classical methods use chemical analysis, but this approach requires relatively expensive laboratory equipment. By contrast, the system proposed in this paper captures image signals from samples and uses an intelligent classification technique to recognize the wood type and the aging time. The classification system uses an ensemble of classifiers obtained from different wavelet decompositions. Each classifier is obtained with different wavelet transform settings. We compared the proposed approach with classical methods based on chemical features. We analyzed 105 samples that had been aged for 3 years and we showed that the proposed solution could automatically recognize wood types and the aging time with an accuracy up to 100.00% and 85.71% respectively, and our method is also cheaper.application/pdfen_ENA feasibility cachaca type recognition using computer vision and pattern recognitionRodrigues, Bruno UrbanoSoares, Anderson da SilvaCosta, Ronaldo Martins daVan Baalen, J.Salvini, Rogério LopesSilva, Flávio Alves daCaliari, MárcioCardoso, Karla Cristina RodriguesRibeiro, Tânia Isabel MonteiroDelbem, A.C.B.Federson, F.M.Coelho, C.J.Laureano, G.T.Lima, T.W.HostingInstitutionOrganizationalBiblioteca Digital do IPBe-mailmailto:dspace@ipb.ptdspace@ipb.ptISSNIsPartOf0168-1699DOIIsPartOf10.1016/j.compag.2016.03.0202018-01-25T10:00:00Z20162016-01-01T00:00:00ZHandlehttp://hdl.handle.net/10198/15503http://purl.org/coar/access_right/c_abf2open accessComputer visionDrinksPattern recognition605031 bytesliteraturehttp://purl.org/coar/resource_type/c_6501journal articlehttp://purl.org/coar/access_right/c_abf2application/pdffulltexthttps://bibliotecadigital.ipb.pt/bitstreams/4546bea5-5ae9-480d-a333-1963a3ae0981/download |
| spellingShingle | A feasibility cachaca type recognition using computer vision and pattern recognition Rodrigues, Bruno Urbano Computer vision Drinks Pattern recognition |
| status | SINGLETON |
| subject.fl_str_mv | Computer vision Drinks Pattern recognition |
| title | A feasibility cachaca type recognition using computer vision and pattern recognition |
| title_full | A feasibility cachaca type recognition using computer vision and pattern recognition |
| title_fullStr | A feasibility cachaca type recognition using computer vision and pattern recognition |
| title_full_unstemmed | A feasibility cachaca type recognition using computer vision and pattern recognition |
| title_short | A feasibility cachaca type recognition using computer vision and pattern recognition |
| title_sort | A feasibility cachaca type recognition using computer vision and pattern recognition |
| topic | Computer vision Drinks Pattern recognition |
| topic_facet | Computer vision Drinks Pattern recognition |
| url | http://hdl.handle.net/10198/15503 |
| visible | 1 |