Abstract:
The proposed work in this presented paper aims to identify and classify the rose species
from the rose image. In my research title “Species Identification and Classification of
Rose Flower Images Using Convolutional Neural Network and K-Means Clustering
Algorithm”, this experiment is conducted with a k-means clustering algorithm and
convolutional neural network. The proposed work in this presented paper aims to identify
and classify the rose species such as Old Garden and New Garden from the rose flower
images. The experiment is conducted with a k-means clustering algorithm and
convolutional neural network. The proposed work is approached in two ways. Firstly, the
rose images are preprocessed by Adobe Photoshop. Secondly, the rose images are
segmented multiple K values by the k-means clustering algorithm so that defective leaves
are accurately recognized for classification. Furthermore, the K-means segmented images
(k=8) and normal preprocessed images are employed by the classifier algorithm named
convolutional neural network. As a result, the K cluster value (k=8) and normal
preprocessed images give the accuracy that is 72% and 73% respectively. Finally, the
results are compared with respect to the K cluster value and normal preprocessed image
that extracted the standard normal preprocessed. The normal preprocessed image gives 1%
better accuracy than the k-means cluster segmented image.
