mage fusion based on fuzzy sets The fuzzy logic approach is widely used in image process-ing. The fuzzy logic gives decision rules and fusion motivation for image fusion [17]. the two inputs images are converted into membership values based on a set of predefined MFs, where the degree of membership of each input pixel to a fuzzy set is determined. Then, the fusion operators are applied to the fuzzified images. The fusion results are then converted back into pixel values using defuzzification. 1)
Image Segmentation Image segmentation attempts to separate an image into its object classes. Clustering methods, edge based methods, histogram-based methods, and region growing methods offer different advantages and disadvantages. The use of a Gaussian mixture expectation maximization (EM) method has been investigated to realize segmentation specifically for x-ray luggage scans [131]. Namely, k Gaussian distributions are added to best fit the image histogram, with each Gaussian distribution corresponding
basically of two types based on the use of a biometric trait for identification and verification. The types of biometric system are • Unimodal biometric system • Multimodal biometric system The Unimodal system has an only single source of information for authorization of a valid user. But sometimes single trait do not provide good quality of sample due to deformations problem in a biometric trait such as the same sample of hand geometry do not capture after swelling, face images changes