ABSTRACT
This chapter proposes a novel approach for creating a multimodal biometric system. The multimodal biometric watermarking system using multiple sources of information has been widely recognized. The best fused template is applied as input along with the cover image to the different watermarking models, such as the genetic algorithm (GA) and bacterial foraging optimization algorithm (BFOA). The proposed work describes the feature extraction of multimodal biometric images such as fingerprint, palmprint, and iris. The chapter explains individual extraction of iris and palmprint modalities. Iris recognition is an automated method of biometric identification that uses mathematical pattern-recognition techniques on video images of the irises of an individual's eyes, whose complex random patterns are unique and can be seen from some distance. In this research work, segmentation of iris is the first phase of iris extraction. Principal component analysis (PCA) is a mathematical tool that changes various correlated variables into a number of uncorrelated variables.
