Leaf Image Recognition Based Identification of Plants: Supportive Framework for Plant Systematics

Abstract:

Plant life is incomplete without proper leaf orientation and morphology. Leaf is the first identity of any plant species. Identification of leaf is the first choice for plant taxonomist as well as common men. Generally, taxonomists and common people face difficulties of different nature during plant identification. Botanists are overwhelmed with fresh data e.g. DNA sequencing to the complex appearance of traits, species phylogeny, environmental influences and outcomes, molecular phenotyping etc. Advancements in biological sciences over last three decades and amplified significance of determining the relationship between structure and function have proved worth of imaging technology as an emerging discipline. Leaf image classification is the best choice for plant taxonomy. Generally, one can easily make over the images of leaves to a system and that computer automatically generates attributes by processing images. Earlier, input images were first converted into grayscale and then transformed to a binary image. Other than plant classification studies with help of image recognition, the same technique can be very supportive for detecting diseased plants in a field. In this article, we have focused on the developments related to image processing and its implementation for plant science research. Leaf image processing has been focused with the help of reported literature in related scientific domains.

Keywords:

Biological research, Image processing, Plants, Systematics.

Citation:

Fida, F., Talib, M.R., Fida, F., Iqbal, M., Aqeel, M., Iqbal, M.N., Noman, A., 2018. Leaf Image Recognition Based Identification of Plants: Supportive Framework for Plant Systematics. PSM Biol. Res., 3(3): 125-131.


 


Author: Fiza Fida, Muhammad Ramzan Talib, Faiza Fida, Naeem Iqbal, Muhammad Aqeel, Muhammad Naeem Iqbal, Ali Noman

Pages: 125-131

Published Online: Aug. 09, 2018

Article Type: Review Article

Views: 238

Downloads: 0