Introduction to the Methods

In this book four new methods are proposed. In the first method the generalized type-2 fuzzy logic is combined with the morphological gradient technique. The second method combines the general type-2 fuzzy systems (GT2 FSs) and the Sobel operator; in the third approach the methodology based on Sobel operator and GT2 FSs is improved to be applied on color images. In the fourth approach, we proposed a novel edge detection method where, a digital image is converted to a generalized type-2 fuzzy image. In this book it is also included a comparative study of type-1, interval type-2 and generalized type-2 fuzzy systems as tools to enhance edge detection in digital images when used in conjunction with the morphological gradient and the Sobel operator. The proposed generalized type-2 fuzzy edge detection methods were tested with benchmark images and synthetic images, in a grayscale and color format.

Application in Face Recognition

Another contribution in this book is that the generalized type-2 fuzzy edge detector method is applied in the preprocessing phase of a face recognition system; where the recognition system is based on a monolithic neural network. The aim of this part of the book is to show the advantage of using a generalized type-2 fuzzy edge detector in pattern recognition applications.

Goals and Advantages

The main goal of using generalized type-2 fuzzy logic in edge detection applications is to provide them with the ability to handle uncertainty in processing real world images; otherwise, to demonstrate that a GT2 FS has a better performance than the edge detection methods based on type-1 and type-2 fuzzy logic systems.