Publication: Classification of fruits using Probabilistic Neural Networks - Improvement using color features
| dc.citedby | 25 | |
| dc.contributor.author | Mustafa N.B.A. | en_US |
| dc.contributor.author | Arumugam K. | en_US |
| dc.contributor.author | Ahmed S.K. | en_US |
| dc.contributor.author | Sharrif Z.A.Md. | en_US |
| dc.contributor.authorid | 57191952020 | en_US |
| dc.contributor.authorid | 54977516700 | en_US |
| dc.contributor.authorid | 25926812900 | en_US |
| dc.contributor.authorid | 6507195893 | en_US |
| dc.date.accessioned | 2023-12-29T07:47:00Z | |
| dc.date.available | 2023-12-29T07:47:00Z | |
| dc.date.issued | 2011 | |
| dc.description.abstract | This paper presents a novel approach for the development of an intelligent fruit sorting system using techniques from Digital Image Processing and Artificial Neural Networks. The aim is to develop a fast and effective classification method along with a target of 100% efficiency. Five fruits; i.e., apples, bananas, carrots, mangoes and oranges were analysed and seventeen features were extracted based on the fruits' morphological and colour characteristics. A regular digital camera was used to acquire the images, and all manipulations were performed in a MATLAB/SIMULINK environment. The results obtained were a significant improvement over a previous study. � 2011 IEEE. | en_US |
| dc.description.nature | Final | en_US |
| dc.identifier.ArtNo | 6129105 | |
| dc.identifier.doi | 10.1109/TENCON.2011.6129105 | |
| dc.identifier.epage | 269 | |
| dc.identifier.scopus | 2-s2.0-84856849332 | |
| dc.identifier.spage | 264 | |
| dc.identifier.uri | https://www.scopus.com/inward/record.uri?eid=2-s2.0-84856849332&doi=10.1109%2fTENCON.2011.6129105&partnerID=40&md5=02bbe27e7a0fcad427202b17a368f4e0 | |
| dc.identifier.uri | https://irepository.uniten.edu.my/handle/123456789/30354 | |
| dc.pagecount | 5 | |
| dc.source | Scopus | |
| dc.sourcetitle | IEEE Region 10 Annual International Conference, Proceedings/TENCON | |
| dc.subject | Colour Recognition | |
| dc.subject | Fruit Classification | |
| dc.subject | HSI | |
| dc.subject | Morphological Feature Analysis | |
| dc.subject | PNN | |
| dc.subject | RGB | |
| dc.subject | Color | |
| dc.subject | Feature extraction | |
| dc.subject | Image processing | |
| dc.subject | Neural networks | |
| dc.subject | Classification methods | |
| dc.subject | Color features | |
| dc.subject | Fruit sorting | |
| dc.subject | HSI | |
| dc.subject | MATLAB/Simulink environment | |
| dc.subject | Morphological features | |
| dc.subject | PNN | |
| dc.subject | Probabilistic neural networks | |
| dc.subject | RGB | |
| dc.subject | Fruits | |
| dc.title | Classification of fruits using Probabilistic Neural Networks - Improvement using color features | en_US |
| dc.type | Conference Paper | en_US |
| dspace.entity.type | Publication |