Imagery characteristics analysis for sorting fresh mallow (corchorusolitorius) leaves
Abstract: Development in the computer world has led to the solution of many problems in the agricultural field. Classification and sorting of vegetables is one of the complex fields that require great human experience. Emergence of new technologies can contribute for problem solving, such as machine visions. As Jew's mallow is a leafy vegetable that is very sensitive to environmental conditions and rapidly deteriorate after harvesting, So it is necessary to configure out a suitable proof of concept for that visual sorting in processing plants. In the present study, wide ranges of Jew's mallow's leaves were selected in terms of severity of greenness, which varied due to different circumstances. An optical meter was used to measure the Chlorophyll Content Index, CCI, for each leaf. Experiments were carried out in November 2019 at the Laboratory of Department of Horticulture, Faculty of Agriculture, Kafrelsheikh University. The experimental procedures were performed in three stages. The ?rst stage, a primary classi?cation is made by CCI-based that are further converted to wilting percent. The second stage, digital Red, Green, and Blue (RGB) camera is used for image capturing for each leaf sample class. Then a scale for leaves images from freshness to wilting is established according to General Appearance (GA) rules and wilting percent. After which the classified leaves images of Corchorusolitoriusare imagery processed to extract characteristic features among the predetermined classes. Morphological analysis shows a significant difference among classes and RGB pixel intensity distribution on grey scale from 0 (pure white) to 255 (pure black) can potentially differentiate among classes according to RGB intensities on the scale. Based on the statistical analysis of pixel intensity distribution of each image, a developed non-linear multiple regression equation (R2=0.99) can predict precisely the wilting percent of the leaf. Eventually the color gradient model can be used effectively to discriminate the leaf color of green, yellow and dark.
Publication year 2021
Pages 61-68
Organization Name
serial title Agricultural Mechanization in Asia, Africa and Latin America
Author(s) from ARC
External authors (outside ARC)
    سعيد الشحات عبد الله كلية الزراعة - جامعة كفر الشيخ
    وائل محمد المسيري كلية الزراعة - جامعة كفر الشيخ
Publication Type Journal
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