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Image data mining
can be done manually by slicing and dicing the data until a
pattern becomes obvious. Or, it can be done with programs that
analyse the data automatically. Colour, texture and shape of
an image have been primitive image descriptors in Content
Based Image Retrieval (CBIR) system. Primitive features of an
image used to identify and retrieve closely matched images
from an image database. It is very difficult to extract images
manually from image database because they are very large.
This paper
presents a novel framework for texture information of an image
and achieves higher retrieval efficiency than the shape
features of an image. There is a trade-off between accuracy
and computational cost. The trade-off decreases as more
efficient algorithm is used to solve the problem and increases
the computational power and will decreases the cost of the
whole system as well. | 
