Cancer Curing Medical Leaves using Texture Image Characteristics
A. Hema Deepika1, N. M. Elango2
1A. Hema Deepika*, School of Information Technology and Engineering, Vellore Institute of Technology Vellore, India.
2N. M. Elango, School of Information Technology and Engineering, Vellore Institute of Technology. Vellore, India.
Manuscript received on September 18, 2019. | Revised Manuscript received on October 20, 2019. | Manuscript published on October 30, 2019. | PP: 6088-6090 | Volume-9 Issue-1, October 2019 | Retrieval Number: A1961109119/2019©BEIESP | DOI: 10.35940/ijeat.A1961.109119
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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: The present day frame work of medical science of India and abroad clearly signals a drift inducing a general direction and turdencoy towards ayurvedic the medicines and formulations over other conventional medical streams. As a result elaborate and heightened efforts are undertaken to revamp the long forgotten herbal formulations over practiced by the great ayurvedic acharyas of this sub continent which acclaimed trustworthiness, effectiveness, and a sure cure for various diseases when the conventional medicines failed to make a headway. The side effects produced by conventional medicines were found to be in excess, where as the herbal formulations were found to have no significant side effects, As such the modern scientists, physicians, and even herbalists are streamlining their effort to formulate herbal medicines and drugs to cure various dreaded diseases like cancer. This research work proposes an innovative and novel process of analyzing cancer curing medical leaves that are available in India .The statistical texture analysis of the leaf is formulated by correlation, homogeneity, contrast, entropy, and smoothness and the result of such analysis is shown.
Keywords: Texture Analysis, Correlation, Homogeneity, Smoothness, Contrast, Entropy, Cancer Curing Species.