Tomatoes selection system based on fruit maturity level using digital color analysis method

Theodore G. Chandra; Kevin G. Erwandha; Aditya Y.; Bina A. Priyantari; Fitriani D.; Muhammad H. Hakim; Achmad S. Hidayat; Agus M. Hatta; Ninik Irawati

doi:10.1117/12.2504987

11 April 2019 Tomatoes selection system based on fruit maturity level using digital color analysis method

Theodore G. Chandra, Kevin G. Erwandha, Aditya Y., Bina A. Priyantari, Fitriani D., Muhammad H. Hakim, Achmad S. Hidayat, Agus M. Hatta, Ninik Irawati

Author Affiliations +

Proceedings Volume 11044, Third International Seminar on Photonics, Optics, and Its Applications (ISPhOA 2018); 110440C (2019) https://doi.org/10.1117/12.2504987
Event: Third International Seminar on Photonics, Optics, and Its Applications (ISPhOA 2018), 2018, Surabaya, Indonesia

Abstract

Tomatoes that are being distributed to the market require certain level of maturity. Determination of maturity requires classification. Automatic tomato classification is the process of sorting tomatoes into different classes using machine vision and image processing. Tomatoes have two types of pigments used for photosynthesis. In the early stage of maturity, tomatoes are green color due to high chlorophyll level. As the tomatoes mature, chlorophyll will dissolve and begin to disappear. The loss of chlorophyll, the lycopene that has a red color will be clearly visible on the tomatoes. The color system used is RGB, then threshold, color analysis, and the final step is the perception of color. It can be concluded that image processing can be used to determine the selection of tomato maturity based on the color. Variables that can be used to determine the maturity level of tomatoes is the ration of the RGB value obtained by the image.

Citation Download Citation

Theodore G. Chandra, Kevin G. Erwandha, Aditya Y., Bina A. Priyantari, Fitriani D., Muhammad H. Hakim, Achmad S. Hidayat, Agus M. Hatta, and Ninik Irawati "Tomatoes selection system based on fruit maturity level using digital color analysis method", Proc. SPIE 11044, Third International Seminar on Photonics, Optics, and Its Applications (ISPhOA 2018), 110440C (11 April 2019); https://doi.org/10.1117/12.2504987

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available

Members: $17.00

Non-members: $21.00 ADD TO CART

PROCEEDINGS
4 PAGES

DOWNLOAD PAPER SAVE TO MY LIBRARY

GET CITATION

RIGHTS & PERMISSIONS

Get copyright permission Get copyright permission on Copyright Marketplace

KEYWORDS

Image processing

RGB color model

Light sources and illumination

Light emitting diodes

Image classification

Cameras

Feature extraction

Show All Keywords

Keywords/Phrases

Search In:

Publication Years