| dc.description.abstract | Abstract: Plant plays a vital role in the
environment. Nature has enormous
members of plants, identifying them and
classifying them is an important task for
botanists. They are still finding difficulties in
recognizing those plants and it is complex,
time-consuming, and due to the use of
specific botanical terms, frustrating for the
non-experts. There are various ways to
recognize a plant, like a flower, root, leaf,
fruit, etc. But usually, plants are recognized
by leaf and their characteristics like shape,
texture, vein structure, color, etc. The
availability of relevant technologies, such as
digital cameras, new techniques in image
processing and pattern recognition thoughts,
leads to researching plant leaf recognition
systems using image processing techniques
rather than using the other parts of the
plants. Searching of research papers related
to the domain was done in the IEEE computer
society digital library, Springer Link, Science
Direct, ACM Digital Library, Academia, and
other research sites using the search terms
like plant leaf identification, plant leaf
prediction, plant leaf classification, plant leaf
recognition, and image processing
techniques. Then started to work on the
Systematic Literature Review (SLR) with
forty research papers; out of forty, most
articles are related and some are not related.
Then these articles are filtered and sorted to
SLR. Nineteen papers which are published in
the past ten years and mostly related to my
topic and methodology, were selected to
perform SLR. Then the methodologies of the
studies were analyzed to identify different
preprocessing and feature extraction
methods that researches have employed to
identify leaves. Then classification accuracy
was compared with related papers and
traced the optimal range of the accuracy for
leaf recognition, which will be the benching
accuracy level for the suggested study. | en_US |
