Blight segmentation on corn crop leaf using connected component extraction and CIELAB color space transformation

Interpretation of human to identify the disease on corn crop is must be tested in laboratory to get more accurate result. Disease infection is caused by microorganism in the leaf of corn crop makes a huge loss in the harvest of corn. Identification of blight in leaf of corn crop can be helped by seg...

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Bibliographic Details
Published in2017 International Seminar on Application for Technology of Information and Communication (iSemantic) pp. 205 - 208
Main Authors Sukmana, Septian Enggar, Rahmanti, Farah Zakiyah
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.10.2017
Subjects
Agriculture
bioinformatic
blight square area
CIE a
Diseases
Feature extraction
Image color analysis
Image segmentation
Labeling
labelling
Seminars
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Summary:Interpretation of human to identify the disease on corn crop is must be tested in laboratory to get more accurate result. Disease infection is caused by microorganism in the leaf of corn crop makes a huge loss in the harvest of corn. Identification of blight in leaf of corn crop can be helped by segmentation process. One of solution is exploiting transformation of RGB color space to CIElab to make a same image perception from different device. This activity uses thirty images of leaf, based on experiment it shows that the most suffering leaf is the tenth data where the largest blight is found in that leaf.
DOI:10.1109/ISEMANTIC.2017.8251870