Envisaging Variance Amid Indian Floras Owed To Contaminates Via SSIM Technique

IJEP 41(9): 1019-1026 : Vol. 41 Issue. 9 (September 2021)

Shilpi Aggarwal1, Madhulika Bhatia2*, Hari Mohan Pandey3 and Rosy Madaan1

1. Manav Rachna International Institute of Research and Studies, Faridabad, Haryana, India
2. Amity University, Noida, Uttar Pradesh, India
3. Edge Hill University, Department of Computer Science, Lancashire, United Kingdom


Earth’s atmosphere contains 20.9% of oxygen among all components (nitrogen, argon and other gases). But due to several factors, such as pollution, global warming, fuel burning, etc., the level of oxygen is degrading. Several researchers have reported that pollution is the main cause for degradation of oxygen levels. People are struggling with several health issues, like asthma, lung cancer and skin problems, like atopic dermatitis, eczema, psoriasis or acne, skin cancer, etc. Due to pollution plants are also getting affected in addition to human beings. Henceforth, numerous researches are in an improvement to overcome the existing challenges. In order to detect the changes in plants due to pollution the current research proposed a structural similarity index methodology (SSIM). All the samples (Ocimum tenuiflorum, Sansevieria trifasciata, Chlorophytum comosum, Azadirachta indica, aloe vera) were stipulated from the Indian species of plants that are rich in oxygen. The structural similarity index (SSIM) is calculated from the input sample images with the help of image processing by using MATLAB 2019a. Further, we have shown the effect on plants due to pollution by contrasting the structural similarity index (SSIM) value with the pollution index. This pollution index was measured from the air quality checker system situated near the target site at the time when the sample images were collected. Many analyses are done and the results were evaluated by plotting graph. This graph depicts that when structural similarity index value increases with respect to pollution index, the image quality of the sample decreases and vice versa.


Structural similarity index methodology, Air quality index, Image processing, Pollution, Oxygen, Plants


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