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160 Chapter 6 Plant leaf disease classification based on feature selection
Figure 6.4 An example of rescaling and center alignment for a leaf image:
(A) original image; (B) corresponding image with bounding box; (C) final
rescaled and center-aligned image.
Due to various contrasts in leaf region, the contrast enhance-
ment method in Refs. [13] is used to change pixel intensities that
benefit in case of providing more information in some areas of an
image. The image data set will be divided into two subsets:
training set and test set. Finally, the convolution neural network
is applied to classify the given images.
Many contrast enhancement methods have been widely
applied to improve the quality of the image [12]. In this chapter,
to ameliorate features that are low contrast to achieve improve-
ment in terms of contrast quality, we use a contrast enhance-
ment approach in Ref. [13] before further analysis. The main
idea of this method is to preserve the mean brightness of an
input image during contrast adjustment in local regions. Firstly,
the input image in RGB color channels is converted into HSI
ones. This approach only focuses on the intensity parameter