Plant Classification Using Firefly Algorithm and Support Vector Machine

The importance of plants for survival of all living beings as well as the humans’ agricultural needs is great as the identification and classification have a key role for their use. Plants are recognized by leaf, flower, or fruit and linked to their suitable cluster. Classification methods are used to isolate and select traits that help identify plants. An automated approach aims to help farmers grow crops easier and better. Computer vision technologies have attracted significant interest in precision agriculture in recent years. This research proposed an approach based on swarm intelligence algorithms and support vector machines to extract features and classify plant images. The nature-inspired firefly algorithm models mating patterns of fireflies, and adapts them to optimization problems for which it excels at resolving. Combined with support vector machines methods, that are often used for solving classification problems with great accuracy, this work proposes a novel approach used to handle plant identification.