Estimation of Percentage of Adulteration using Structural Similarity Index
Bharath Surianarayanan1, Sridhar Pandian A2, Sathiya Narayanan3, Jani Anbarasi L4, Benson Edwin Raj5
1Bharath Surianarayanan*, School of Electronics Engineering (SENSE), Vellore Institute of Technology, Chennai (Tamil Nadu), India.
2Sridhar Pandian A, School of Electronics Engineering (SENSE), Vellore Institute of Technology, Chennai (Tamil Nadu), India.
3Sathiya Narayanan*, School of Electronics Engineering (SENSE), Vellore Institute of Technology, Chennai (Tamil Nadu), India.
4Jani Anbarasi L, School of Computing Science and Engineering (SCSE), Vellore Institute of Technology, Chennai (Tamil Nadu), India.
5Benson Edwin Raj, Department of Computer Information Sciences, Higher Colleges of Technology, Fujairah, United Arab Emirates (UAE).
Manuscript received on November 15, 2019. | Revised Manuscript received on 20 November, 2019. | Manuscript published on December 10, 2019. | PP: 2129-2132 | Volume-9 Issue-2, December 2019. | Retrieval Number: B7326129219/2019©BEIESP | DOI: 10.35940/ijitee.B7326.129219
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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: Adulteration in food supplies to reduce the cost and thereby compromising in its quality is an ever-growing problem in the food industry. In the past, adulteration estimation was done using chemicals and infrared spectroscopy methods. In this paper, adulteration estimation of chili powder contaminated with brick powder is done by means of Structural Similarity (SSIM) Index and the performance for various levels of contamination is evaluated. SSIM provides a measure of structural similarity between two images i.e. test image and reference image. This work has been carried out to identify contamination in a given sample of chili powder and estimate the approximate level of contamination. Experimental results show that SSIM measure provides an accurate estimate of the degree of contamination.
Keywords: Computerized Adulteration, Luminance masking, Pseudo Noise Ratio, Structural Similarity.
Scope of the Article: Structural Engineering