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Starfruit Color Maturity Classification Using Cr as Feature

Authors: R. Amirulah; M. M. Mokji; Zuwairie Ibrahim;

Starfruit Color Maturity Classification Using Cr as Feature

Abstract

The quality inspection for export star fruit is still perform manually by human labor until today. Due to manual process, a real-time system for star fruit color maturity inspection is developed in this paper. In real-time application, most of the image acquisition device is using YCbCr color space data such as CCD camera. This paper presents the modification on the previous star fruit color maturity classification algorithm which is based on RGB color space into YCbCr color space. In this new modified algorithm, the system is faster than before because the star fruit maturity classification process operates without any mathematical operation involved in the feature extraction process. This process is possible as the color information can be obtained directly from the Cb and Cr component which is not the case in the RGB color space. Based on the experiment results, the classification accuracy for the modified algorithm is 96%.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
7
Average
Top 10%
Average
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