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Figure 1. Content-based image classification and retrieval architecture
Definition 1 (Descriptor). Using a co-occurrence matrix, different properties of the pixel distribution
can be obtained by applying mathematical operations to the matrix values. These operations are called
descriptors. Each descriptor is related to a particular visual feature about the texture.
Haralick et al. proposed a set of 14 descriptors (Haralick, 1979) derived from the co-occurrence
matrix. In this paper, five features (descriptors) were selected for further study: maximum probability
( MP ), contrast ( Cont ), inverse different moment ( IM ), angular second moment ( AM ), and entropy ( En-
tro ). Where:
Maximum probability ( MP ) is defined as follows:
,
(8)
MP
=
max
P i j
( , )
i j
,
Contrast feature is a measure of the image contrast or the number of local variations is present in
an image. It takes the following form:
2
,
(9)
Cont
=
(
i j P i j
) ( , )
i j
,
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