| _version_ |
1860797158722109440
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| building |
INTELEK Repository
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| collection |
Online Access
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| collectionurl |
https://intelek.unisza.edu.my/intelek/pages/search.php?search=!collection407072
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| date |
2018-12-31 15:34:36
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| format |
Restricted Document
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| id |
11598
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| institution |
UniSZA
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| originalfilename |
5857-01-FH02-FIK-19-23969.pdf
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| person |
Amalina
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| recordtype |
oai_dc
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| resourceurl |
https://intelek.unisza.edu.my/intelek/pages/view.php?ref=11598
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| spelling |
11598 https://intelek.unisza.edu.my/intelek/pages/view.php?ref=11598 https://intelek.unisza.edu.my/intelek/pages/search.php?search=!collection407072 Restricted Document Article Journal application/pdf 8 1.6 Adobe Acrobat Pro DC 20 Paper Capture Plug-in Amalina 2018-12-31 15:34:36 5857-01-FH02-FIK-19-23969.pdf UniSZA Private Access Histogram-Based Detection of Tomato Maturity: A Preliminary Study Malaysian Journal of Computing and Applied Mathematics Color is one of the most important features of images. Estimating the ripeness of fruits via color can be performed as it is the dominant feature in describing the information of image. However, each of color model has given different performance when used in experiment. This paper reports a preliminary study to identify the ripeness of tomato by extracting the color features and compute into Histogram based method. Histogram proposes the number of color intensities in ROI (Region of Interest) or a whole image to give more possibilities result. Histogram based techniques merely count the number or frequency of pixels in an image. The output value of color model will be used as an input to the classifier in future works. Similarity measures such as Euclidean distance, City Block, Manhattan distance or Histogram Intersection will be explored to calculate the image similarity rating. 1 2 21-28
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| spellingShingle |
Histogram-Based Detection of Tomato Maturity: A Preliminary Study
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| summary |
Color is one of the most important features of images. Estimating the ripeness of fruits via color can be performed as it is the dominant feature in describing the information of image. However, each of color model has given different performance when used in experiment. This paper reports a preliminary study to identify the ripeness of tomato by extracting the color features and compute into Histogram based method. Histogram proposes the number of color intensities in ROI (Region of Interest) or a whole image to give more possibilities result. Histogram based techniques merely count the number or frequency of pixels in an image. The output value of color model will be used as an input to the classifier in future works. Similarity measures such as Euclidean distance, City Block, Manhattan distance or Histogram Intersection will be explored to calculate the image similarity rating.
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| title |
Histogram-Based Detection of Tomato Maturity: A Preliminary Study
|
| title_full |
Histogram-Based Detection of Tomato Maturity: A Preliminary Study
|
| title_fullStr |
Histogram-Based Detection of Tomato Maturity: A Preliminary Study
|
| title_full_unstemmed |
Histogram-Based Detection of Tomato Maturity: A Preliminary Study
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| title_short |
Histogram-Based Detection of Tomato Maturity: A Preliminary Study
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| title_sort |
histogram-based detection of tomato maturity: a preliminary study
|