Automated Plant Recognition System with Geographical Position Selection for Medicinal Plants

Algorithm 1

Morphological algorithm-based nearest plan detection.

	Step 1: Images of the leaf are taken with a high-resolution camera.
	Step 2: The images are converted to jpeg format to process them to extract information.
	Step 3: Android Studio integrated with OpenCV libraries is used as a platform to develop the application.
	Step 4: Using OpenCV, the program is coded in Java to extract all leaf details like edge, color, area, texture, and shape. This is done using a neural network morphological algorithm.
	Step 5: The image data is uploaded to the database with other information and the importance of the plant.
	Step 6: For each plant species, geographical locations in the form of latitude and longitude are stored in a database. If complexity arises in matching, further analysis can be done using prediction algorithms. The locating is done by creating a database consisting of all the latitudes and longitudes for each specific species, and then it is queried to show the geotags through Google Maps. This can be done by passing the values in arrays in a function.
	Step 7: Google API is used to fetch the nearest location of the species during a search using minimum distance algorithms.