Shape classification of Sunshine mango using machine vision
Access is limited to UniMAP community.
Saved in:
| Main Author: | |
|---|---|
| Other Authors: | |
| Format: | Other |
| Language: | English |
| Published: |
Universiti Malaysia Perlis (UniMAP)
2022
|
| Subjects: | |
| Online Access: | http://dspace.unimap.edu.my:80/xmlui/handle/123456789/73281 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Institution: | Universiti Malaysia Perlis |
| Language: | English |
| id |
my.unimap-73281 |
|---|---|
| record_format |
dspace |
| spelling |
my.unimap-732812022-01-11T04:43:06Z Shape classification of Sunshine mango using machine vision Nur Athirah, Mabasri School of Bioprocess Engineering Shape Classification Sunshine Mango Machine vision Access is limited to UniMAP community. This thesis presents the application of machine vision to classify the shape regularity of sunshine mango. The algorithm were successfully developed and programmed for image processing and image acquisition and then the regular and misshapen mangoes were able to classify using discriminant analysis. Using the acquired images from mangoes with different shapes, some essential geometrical features such as length, width, perimeter, area, major axis and minor axis were extracted from each image. Four size-shape parameter, area ratio, aspect ratio, circularity and compactness were used to analyse the mangoes between regular and misshapen. Based on discriminant analysis, three size-shape parameter (area ratio, aspect ratio, and circularity) were found to be effective in differentiate the regular and misshapen of mangoes. Overall the algorithm from discriminant analysis were able to classify 74% success rate to differentiate the regular and misshapen mangoes. 2022-01-11T04:43:06Z 2022-01-11T04:43:06Z 2017-06 Other http://dspace.unimap.edu.my:80/xmlui/handle/123456789/73281 en Universiti Malaysia Perlis (UniMAP) |
| institution |
Universiti Malaysia Perlis |
| building |
UniMAP Library |
| collection |
Institutional Repository |
| continent |
Asia |
| country |
Malaysia |
| content_provider |
Universiti Malaysia Perlis |
| content_source |
UniMAP Library Digital Repository |
| url_provider |
http://dspace.unimap.edu.my/ |
| language |
English |
| topic |
Shape Classification Sunshine Mango Machine vision |
| spellingShingle |
Shape Classification Sunshine Mango Machine vision Nur Athirah, Mabasri Shape classification of Sunshine mango using machine vision |
| description |
Access is limited to UniMAP community. |
| author2 |
School of Bioprocess Engineering |
| author_facet |
School of Bioprocess Engineering Nur Athirah, Mabasri |
| format |
Other |
| author |
Nur Athirah, Mabasri |
| author_sort |
Nur Athirah, Mabasri |
| title |
Shape classification of Sunshine mango using machine vision |
| title_short |
Shape classification of Sunshine mango using machine vision |
| title_full |
Shape classification of Sunshine mango using machine vision |
| title_fullStr |
Shape classification of Sunshine mango using machine vision |
| title_full_unstemmed |
Shape classification of Sunshine mango using machine vision |
| title_sort |
shape classification of sunshine mango using machine vision |
| publisher |
Universiti Malaysia Perlis (UniMAP) |
| publishDate |
2022 |
| url |
http://dspace.unimap.edu.my:80/xmlui/handle/123456789/73281 |
| _version_ |
1724610025878454272 |