Image-based classification and segmentation of healthy and defective mangoes

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creativework.keywordsCNN; Image processing; Machine Learning; Mango Classification; Segmentation
dc.contributor.authorBaculo, Maria Jeseca C.
dc.contributor.authorRuiz, Conrado
dc.date.accessioned2026-08-20T07:25:51Z
dc.date.available2026-08-20T07:25:51Z
dc.date.issued2019
dc.descriptionAbstract only
dc.description.abstractThe use of image processing and classification for agricultural applications has been widely studied and has led to work such as the automatic grading of fruit and vegetables, yield approximation and defect detection. Image segmentation is one of the first steps to identify the region of interest within an image. This paper presents an approach to automatic segmentation and classification of healthy and defective Carabao mangoes. K-means, range filtering and color-channel segmentation were utilized so that the varying texture and color of mangoes due to the surface defects can be considered. Results show that the proposed technique performs better than the classical K-means segmentation. The performance of segmentation step has a considerable influence on the precision of the classification model. Segmented and not segmented images were trained using KNN, SVM, MLP and CNN. The experiments showed that the models performed better when trained with segmented images.
dc.identifier.citationBaculo, M. J. C., & Ruiz, C. (2019). Image-based classification and segmentation of healthy and defective mangoes. In Eleventh International Conference on Machine Vision (ICMV 2018) (Vol. 11041, p. 1104117). SPIE. https://doi.org/10.1117/12.2522840
dc.identifier.doihttps://doi.org/10.1117/12.2522840
dc.identifier.isbn978-151062748-2
dc.identifier.urihttps://lakasa.dmmmsu.edu.ph/handle/123456789/2409
dc.language.isoen
dc.publisherSPIE - The International Society for Optical Engineering
dc.relation.urihttps://www.scopus.com/pages/publications/85063460449?origin=resultslist
dc.sdgSDG 2
dc.sdgSDG 9
dc.sdgSDG 12
dc.subjectMachine learning
dc.subjectFruit--Grading
dc.subject.ddcImage processing
dc.subject.lcshImage segmentation
dc.subject.lcshAgricultural productivity
dc.titleImage-based classification and segmentation of healthy and defective mangoes
dc.typeConference paper
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