ABSTRACT
Soft computing is a group of methodologies that works synergistically to provide flexible information processing capability for handling real-life ambiguous situations. The aim is to exploit the tolerance for imprecision, uncertainty, approximate reasoning, and partial truth in order to achieve tractability, robustness, low-cost solutions, and close resemblance with human-like decision-making. Soft computing methodologies (involving Fuzzy Sets, neural networks, genetic algorithms, Rough Sets, and probabilistic reasoning) have been successfully employed in various image processing tasks, including image segmentation, enhancement, and classification, both individually and
for Video
in combination with other soft computing techniques. The reason for such success has its motivation in the fact that they provide powerful tools to describe uncertainty, naturally embedded in images, which can be exploited in various image processing tasks. The chapter is focused on theories of Rough and Fuzzy Sets, their synergic operations, and their applications in the field of image processing.
