Analysis of Leaf Features in Chili Plants Using Automated Color Equalization (ACE)

 
 
 
  • Abstract
  • Keywords
  • References
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  • Abstract


    Chili is a variety of crop groups that have promising business prospects. To obtain optimal agricultural yield, then the process of plant care and how to planting should be maximal. Constraints often experienced by farmers in the process of planting chili in Magelang regency of Indonesia is a disease of yellow leaves. Some diseases in plants can be identified using precision technology, one of them is by using an image or image-based technology. In previous studies, no one has analyzed using feature extraction using ACE as an analysis to detect plant disease in chili. In this study will extract features using Automated Color Equalization (ACE) which is then classified using SVM (Support Vector Machine) for disease identification based on its leaves. With this method, the accuracy of the extraction results in a combination of 80% texture features, color feature extraction, and a combination of 80% color feature texture

     

     


  • Keywords


    Feature Extraction, Automated Colour Equalization, SVM

  • References


      [1] M. F. Handari, “Implementasi Kebijakan Perlindungan Lahan Pertanian Pangan Berkelanjutan di Kabupaten Magelang.” Program Magister Ilmu Lingkungan Undip, 2012.

      [2] M. T. bin MohamadAzmi and N. M. Isa, “Orchid disease detection using image processing and fuzzy logic,” in Electrical, Electronics and System Engineering (ICEESE), 2013 International Conference on, 2013, pp. 37–42.

      [3] K. Muthukannan, P. Latha, R. P. Selvi, and P. Nisha, “Classification of diseased plant leaves using neural network algorithms,” ARPN J. Eng. Appl. Sci., vol. 10, no. 4, pp. 1913–1919, 2015.

      [4] I. O. Awoyelu and R. O. Adebisi, “A Predictive Fuzzy Expert System for Diagnosis of Cassava Plant Diseases,” 2015.

      [5] R. Masood, S. A. Khan, and M. N. A. Khan, “Plants disease segmentation using image processing,” Int. J. Mod. Educ. Comput. Sci., vol. 8, no. 1, p. 24, 2016.

      [6] S. S. Sannakki, V. S. Rajpurohit, V. B. Nargund, and R. Arunkumar, “Disease identification and grading of pomegranate leaves using image processing and fuzzy logic,” Int. J. food Eng., vol. 9, no. 4, pp. 467–479, 2013.

      [7] R. R et al., “Visual Cryptography with RSA Algorithm for Color Image,” Int. J. Eng. Technol., vol. 7, no. 2.5, pp. 65–68, Mar. 2018.

      [8] T. Listyorini, S. Sallu, A. Iskandar, R. T. Manurung, and A. D. Gs, “Holographic Reflection Penglipuran Village Bali,” Int. J. Eng. Technol., vol. 7, no. 2.12, pp. 216–219, 2018.

      [9] H. Nurdiyanto and R. Rahim, “Enhanced pixel value differencing steganography with government standard algorithm,” in 2017 3rd International Conference on Science in Information Technology (ICSITech), 2017, pp. 366–371.

      [10] R. Rahim, T. Afriliansyah, H. Winata, D. Nofriansyah, Ratnadewi, and S. Aryza, “Research of Face Recognition with Fisher Linear Discriminant,” IOP Conf. Ser. Mater. Sci. Eng., vol. 300, p. 012037, 2018.

      [11] Basiroh, Analisis Cita Daun pada tanaman Cabai menggunakan automated colour Equalization. 2018.


 

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Article ID: 18139
 
DOI: 10.14419/ijet.v7i2.13.18139




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