Teknologi Pengolahan Citra Digital Untuk Ekstraksi Ciri pada Citra Daun untuk Identifikasi Tumbuhan Obat

Trinugi Wira Harjanti(1*), Himawan Himawan(2)

(1) Sekolah Tinggi Teknologi Informasi NIIT
(2) Sekolah Tinggi Teknologi Informasi NIIT
(*) Corresponding Author

Abstract


The leaf image identification process depends on the feature extraction results. Each medicinal plant has different shapes and patterns of leaf venation. But for one type of medicinal plants have the same pattern of venation shape and pattern even though the size is different. One of the methods for extraction of leaf image form characteristics is by fractal-based feature extraction. Through fractal can be calculated the value of leaf dimensions and searched parts of leaves that have similarities between one part with other parts. As for the method of extracting the characteristics of venation pattern using B-Spline method. Benefits of research conducted is to help people identifying the types of medicinal plants found, knowing the benefits and ways of brewing. While the research contribution is prototype software application based on information technology that can be used by the people through mobile phones for the identification of medicinal plants. To identify or match the results of feature extraction on the leaf found whether included in the medicinal plant, conducted by Euclidean Distance method. In the experiments we used 1100 data consist of 55 variety of medicinal plants for each 20 samples.The experimental result show that the accuracy of identification using of fractal and b-spline is 85.30%.


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References


Annisa. 2009. Ekstraksi Ciri Morfologi dan tekstur untuk Temu Kembali Citra Helai Daun.

Barnesley MF, Devaney RL, Mandelbort, Peitgen, Saup D, Voss, RF. 1988. The Science of Fractal Images. Springger verlag.

Bruno OM, Backes AR.2008. A New Approach to Estimate Farctal Dimension of Texture image. ICISP. LNCS:136-143.

Chandra MPS, Reeddy S, Babu Ramesh. 2009. Iris Recognition System Using Fractal Dimension of Haar Patterns. Internasional Journal of Signal Processing 2:75-81.

Herdiyeni Y, Wahyuni N. 2012. Mobile Application for Indonesian Medicinal Plants Identification using Fuzzy local Binary Pattern and Fuzzy Color Histogram. ICACSIS 2012

Hermaduanti N, Kusumadewi S. 2008. Sistem Pendukung Keputusan Berbasis SMS untuk Menentukan Status Gizi dengan Metode K-Nearest Neighbor. Proseding Seminar Nasional Aplikasi Teknologi Informasi 2008, Yogyakarta; 49-55.

Kintoko. 2006. Prospek pengembangan tanaman obat. Prosiding Persidangan Antarbangsa Pembangunan Aceh 26-27 Desember 2006 UKM Bangi

Mandelbort, 1982, The Fractal of Nature, Springer Verlag.

Mozaffari S, Faez K, Kanan HR. 2005. Performance Evaluation of Fractal Feature in recognition of Postal Code Using an RBF neural Network and SVM Classiffier. MVA2005IAPRCATI ; 562-565.

Mulyana I, Herdiyeni Y, Wijaya S H .2013. Identification of Medical Plant Based on Fractal by Using Clustering Fuzzy C-Means. Prosiding ICIBA2013

Ramadhani. 2009. Ekstraksi Fitur Bentuk dan Venasi Citra Daun dengan Pemodelan Fourier dan B-Spline.




DOI: http://dx.doi.org/10.30998/faktorexacta.v14i3.9841

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