Identification of Dayak Onion with Shape and Texture Feature Extraction by Image Processing

Joan Angelina Widians, Anindita Septiarini, Masna Wati, Andi Tejawati, Maratus Soleha, Tjikoa Ade Fiqri

Abstract


Dayak Onion (Eleutherine Palmifolia (L.) Merr) is a medicinal plant that has expanded in East Kalimantan. Humans select the type of onion very quickly, but not for computers. Human perception tends to be subjective to an object because there are factors in the composition of color, shape, and texture owned by the entity thing. The study aims to identify Dayak onions with digital images and apply the K-Nearest Neighbor (KNN) method to extract shape and texture features. There are five types of onions: Dayak onions, Shallot, Bombai onions, Garlic, and Lanang onions. K-Nearest Neighbor (KNN) is a method for objects classification on data learning that is the closest distance or has the most characteristic similarities to an object. This method is for the Dayak Onion’s identification and classification. The accuracy level of the KNN method is on shape and texture feature extraction to identifying Dayak onions using 100 image data. Overall, the best accurate result with the KNN method is 86.66%.

Keywords


Dayak Onion; Shape Feature; Texture Feature; Feature Extraction; K-Nearest Neighbor (KNN); Image Processing

Full Text:

PDF

References


E. Budiman, U. Hairah, Haeruddin, A. Tejawati, S. Darmawan, and S. Wahyuni, “Biodiversity information system of medicinal plants from tropical rainforest Borneo based on traditional knowledge ethnic of Dayak,” Adv. Sci. Lett., vol. 24, no. 11, pp. 8668–8673, 2018, doi: 10.1166/asl.2018.12321.

F. Falah and N. Hadiwibowo, “Species identification of traditional medicine plants for women’s health in East Kalimantan: lesson learned from local wisdom,” Indones. J. For. Res., vol. 4, no. 1, pp. 49–67, 2017.

J. Angelina Widians, M. Wati, A. Tejawati, and E. Budiman, “Biodiversity information system for management of medicinal plants data tropical rainforest Borneo,” Int. J. Eng. Technol., vol. 7, no. 4.44, p. 31, 2018, doi: 10.14419/ijet.v7i4.44.26858.

S. H. Noorcahyati, “Tumbuhan berkasiat obat etnis asli Kalimantan,” Balai Penelit. Teknol. Konserv. Sumber Daya Alam Balikpapan, 2012.

A. Septiarini, H. Hamdani, H. R. Hatta, and A. A. Kasim, “Image-based processing for ripeness classification of oil palm fruit,” in 2019 5th International Conference on Science in Information Technology (ICSITech), 2019, pp. 23–26.

J. A. Widians, N. Puspitasari, and A. Febriansyah, “Disease diagnosis system using certainty factor,” in 2019 International Conference on Electrical, Electronics and Information Engineering (ICEEIE), 2019, vol. 6, pp. 303–308.

E. M. Kuntorini and M. D. Astuti, “Penentuan Aktivitas Antioksidan Ektrak Etanol Bulbus Bawang Dayak,” Sains dan Terap. Kim., vol. 4, no. 1, pp. 15–22, 2010.

M. Apuy, A. M. Lahjie, B. Simarangkir, Y. Ruslim, and R. Kristiningrum, “Traditional plants in forest gardens of West Kutai, Indonesia: Production and financial sustainability,” Biodiversitas J. Biol. Divers., vol. 18, no. 3, pp. 1207–1217, 2017.

E. Budiman, M. Wati, U. Hairah, F. Alameka, and M. Jamil, “Intelligent dDecision support systems of medicinal forest plants for kkin disease,” in 2021 3rd East Indonesia Conference on Computer and Information Technology (EIConCIT), 2021, pp. 354–359.

N. Dengen, E. Budiman, J. A. Widians, M. Wati, U. Hairah, and M. Ugiarto, “Biodiversity information system: Tropical rainforest borneo and traditional knowledge ethnic of dayak,” J. Telecommun. Electron. Comput. Eng., vol. 10, no. 1–9, 2018.

N. Puspitasari, J. A. Widians, E. Budiman, M. Wati, and A. E. Ramadhan, “Dayak Onion (Eleutherine palmifolia (L) Merr) as an alternative treatment in early detection of dental caries using certainty factor,” 2020 3rd Int. Semin. Res. Inf. Technol. Intell. Syst. ISRITI 2020, no. L, pp. 482–487, 2020, doi: 10.1109/ISRITI51436.2020.9315469.

J. A. Widians, H. S. Pakpahan, E. Budiman, H. Haviluddin, and M. Soleha, “Klasifikasi jenis bawang menggunakan metode k-nearest neighbor berdasarkan ekstraksi fitur bentuk dan tekstur,” J. Rekayasa Teknol. Inf., vol. 3, no. 2, p. 139, 2019, doi: 10.30872/jurti.v3i2.3213.

A. Gokhale, S. Babar, S. Gawade, and S. Jadhav, “Identification of medicinal plant using image processing and machine learning,” in Applied Computer Vision and Image Processing, Springer, 2020, pp. 272–282.

A. Septiarini, A. Harjoko, R. Pulungan, and R. Ekantini, “Automatic detection of peripapillary atrophy in retinal fundus images using statistical features,” Biomed. Signal Process. Control, vol. 45, pp. 151–159, 2018.

M. Wati, N. Puspitasari, E. Budiman, and R. Rahim, “First-order feature extraction methods for image texture and melanoma skin cancer detection,” in Journal of Physics: Conference Series, 2019, vol. 1230, no. 1, p. 12013.

A. Septiarini, H. Hamdani, H. Rahmania, and K. Anwar, “Scientia horticulturae automatic image segmentation of oil palm fruits by applying the contour- based approach,” Sci. Hortic. (Amsterdam)., vol. 261, no. November 2019, p. 108939, 2020, doi: 10.1016/j.scienta.2019.108939.

A. Septiarini, A. Sunyoto, H. Hamdani, A. A. Kasim, F. Utaminingrum, and H. R. Hatta, “Machine vision for the maturity classification of oil palm fresh fruit bunches based on color and texture features,” Sci. Hortic. (Amsterdam)., vol. 286, p. 110245, 2021.

A. Marion, Introduction to image processing. Springer, 2013.

A. Septiarini, A. Harjoko, R. Pulungan, and R. Ekantini, “Automated detection of retinal nerve fiber layer by texture-based analysis for glaucoma evaluation,” Healthc. Inform. Res., vol. 24, no. 4, pp. 335–345, 2018.

M. M. P. Petrou and C. Petrou, Image processing: the fundamentals. John Wiley & Sons, 2010.

A. Septiarini, H. Hamdani, H. R. Hatta, and K. Anwar, “Automatic image segmentation of oil palm fruits by applying the contour-based approach,” Sci. Hortic. (Amsterdam)., vol. 261, p. 108939, 2020.

A. A. Kasim, R. Wardoyo, and A. Harjoko, “Batik classification with artificial neural network based on texture-shape feature of main ornament,” Int. J. Intell. Syst. Appl., vol. 11, no. 6, p. 55, 2017.

Y. F. Riti, H. A. Nugroho, S. Wibirama, B. Windarta, and L. Choridah, “Feature extraction for lesion margin characteristic classification from CT Scan lungs image,” in 2016 1st International Conference on Information Technology, Information Systems and Electrical Engineering (ICITISEE), 2016, pp. 54–58.

L. M. Abualigah and A. T. Khader, “Unsupervised text feature selection technique based on hybrid particle swarm optimization algorithm with genetic operators for the text clustering,” J. Supercomput., vol. 73, no. 11, pp. 4773–4795, 2017.


Refbacks

  • There are currently no refbacks.