  In the recent advancement of multimedia technologies, it becomes a major
concern of detecting visual attention regions in the field of image processing.
The popularity of the terminal devices in a heterogeneous environment of the
multimedia technology gives us enough scope for the betterment of image
visualization. Although there exist numerous methods, feature based image
extraction becomes a popular one in the field of image processing. The
objective of image segmentation is the domain-independent partition of the
image into a set of regions, which are visually distinct and uniform with
respect to some property, such as grey level, texture or colour. Segmentation
and subsequent extraction can be considered the first step and key issue in
object recognition, scene understanding and image analysis. Its application
area encompasses mobile devices, industrial quality control, medical
appliances, robot navigation, geophysical exploration, military applications,
etc. In all these areas, the quality of the final results depends largely on
the quality of the preprocessing work. Most of the times, acquiring
spurious-free preprocessing data requires a lot of application cum mathematical
intensive background works. We propose a feature based fuzzy rule guided novel
technique that is functionally devoid of any external intervention during
execution. Experimental results suggest that this approach is an efficient one
in comparison to different other techniques extensively addressed in
literature. In order to justify the supremacy of performance of our proposed
technique in respect of its competitors, we take recourse to effective metrics
like Mean Squared Error (MSE), Mean Absolute Error (MAE) and Peak Signal to
Noise Ratio (PSNR).
