SURF Points Versus SIFT Points in Identification of Medicinal Plants
PL. Chithra1, S. Janes Pushparani2
1PL. Chithra*, Professor Department of Computer Science, University of Madras,Chennai, India.
2S. Janes Pushparani, Assistant Professor, Department of Computer Applications, Ethiraj College for Women, Chennai, India.
Manuscript received on November 25, 2019. | Revised Manuscript received on December 08, 2019. | Manuscript published on December 30, 2019. | PP: 602-607 | Volume-9 Issue-2, December, 2019. | Retrieval Number: A9466109119/2019©BEIESP | DOI: 10.35940/ijeat.A9466.129219
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Today, digital image processing is used in diverse fields; this paper attempts to compare the outcome of two commonly used techniques namely Speeded Up Robust Feature (SURF) points and Scale Invariant Feature Transform (SIFT) points in image processing operations. This study focuses on leaf veins for identification of plants. An algorithm sequence has been utilized for the purpose of recognition of leaves. SURF and SIFT extractions are applied to define and distinguish the limited structures of the documented vein image of the leaf separately and Support Vector Machine (SVM) is integrated to classify and identify the correct plant. The results prove that the SURF algorithm is the fastest and an efficient one. The results of the study can be extrapolated to authenticate medicinal plants which is the starting step to standardize herbs and carryout research.
Keywords: Digital image processing, foliage, herbal, medicinal plants, leaf vein, Scale Invariant Feature Transform (SIFT) points extraction, Speeded Up Robust Feature (SURF) points extraction, Support Vector Machine (SVM) classifier