DETEKSI KADAR NITROGEN DAN KLOROFIL CITRA DAUN MENGGUNAKAN RUANG WARNA HSI

Dody Pernadi

doi:10.35760/ik.2020.v25i1.2573

DETEKSI KADAR NITROGEN DAN KLOROFIL CITRA DAUN MENGGUNAKAN RUANG WARNA HSI

Dody Pernadi
Universitas Gunadarma
Indonesia

DOI: http://dx.doi.org/10.35760/ik.2020.v25i1.2573

Abstract

Kandungan terhadap kadar nitrogen dan klorofil salah satunya dapat ditentukan dari citra daun. Penelitian ini akan menentukan tekstur citra daun berdasarkan nilai Gray Level Co-occurrence Matrix berupa nilai contrast, homogeneity, correlation, energy, dan entropy. Penelitian ini juga akan menghitung kadar nitrogen dan kandungan klorofil daun dengan melakukan pencarian nilai tengah (mean) dari tiap komponen warna RGB yang kemudian ditentukan dengan ruang warna HSI. Hasil ujicoba menunjukkan perhitungan kandungan nitrogen pada citra daun berhasil dilakukan dengan mengekstraksi ruang warna HSI citra daun. Kandungan ini mutlak diperlukan petani dalam menentukan jumlah kadar pemupukan dalam satu jenis tanaman.

Keywords

Daun, GLCM, HSI, Klorofil, Nitrogen

References

Croft H, Chen JM, and Zhang Y, “Temporal disparity in leaf chlorophyll content and leaf area index across a growing season in a temperate deciduous forest”, International Journal of Applied Earth Observation and Geoinformation 33: 312–320, 2014.

P. Karthika, R. Hema karthika, N. Jayachandra, E. Joice rathinam, “Estimation of chlorophyll content in papaya leaf using mathematical operations”, International journal of computer applications, ISSN. 0975-8887, pp-6-11, January 2014.

Agrios GN, “Plant Pathology”, Fifth edition. New York (US): Elsevier Academic Pr. 2005.

Farshad Vesali, Mahmoud Omid, Amy Kaleita, Hossein Mobli, “Development of an android app to estimate chlorophyll content of corn leaves based on contact imaging”, Computers and Electronics in Agriculture, Volume 116, 2015, Pages 211-220, ISSN 0168-1699, 2015.

Yeni Herdiyeni, Elis N Herliyana, "Leaf Morphological Feature Extraction of Digital Image Anthocephalus Cadamba", TELKOMNIKA, Vol.14, No.2, June 2016.

Bo Liu, Yue-Min Yue, Ru Li, Wen-Jing Shen, and Ke-Lin Wang, “Plant Leaf Chlorophyll Content Retrieval Based on a Field Imaging Spectroscopy System”, Sensors Journal, Pp. 19910-19925, ISSN 1424-8220, October 2014.

Anup Vibhute & S.K. Bodhe, "Color Image Processing Approach For Nitrogen Estimation Of Vineyard", International Journal of Agricultural Science and Research (IJASR), ISSN 2250-0057, Vol. 3, Issue 3, Aug 2013.

Utpal Barman, Ridip Dev Choudhury, Arunav Saud, Sushmita Dey, Bijon Kumar Dey, Barna Pratim Medhi and Golap Gunjan Barman, “Estimation Of Chlorophyll Using Image Processing”, International Journal of Recent Scientific Research Research, Vol. 9, Issue, 3(C), pp. 24850-24853, March 2018.

Leena N, K.K Saju, "Classification of Macronutrient Deficiencies in Maize Plant Using Machine Learning", International Journal of Electrical and Computer Engineering (IJECE), Vol. 8, No. 6, December 2018.

Ahsan M, M Dzulkifli, “Features Extraction for Object Detection Based on Interest Point”, TELKOMNIKA Telecommunication, Computing, Electronics and Control, 11: 2716-2722, 2013.

Gonzalez R, Woods, R, Digital Image Processing, Third edition. New Jersey, USA: Pearson Prentice Hall. 2008.

Leaf Image Dataset from GitHub. Source: https://github.com/sahilsobti. access Date February 21 2019.

Fakultas Teknologi Industri