Principal Component Analysis

It has been observed that there are various factors that act as challenges in the process of image recognition like illumination, size, orientation, etc. In recent years, a new view-based approach to image recognition has been developed. In this book, we have analysed Principal Component Analysis, which is one of the most widely used algorithm for image recognition.The origins of PCA lie in multivariate data analysis; however, it has a wide range of other applications. PCA has been called having one of the most important results from applied linear algebra and perhaps its most common use is as the first step in trying to analyse large data sets. An experiment is described which is conducted to classify the images based on training data set of and observing the accuracy and time taken by the algorithm based on principal component analysis.

Autorentext

Prof. Khushi Khanchandani, M.E (Computer Engineering), has been working in K. J. Somaiya College of Engineering, one of the most reputed Engineering colleges in Mumbai. She has a teaching experience of 12+ years for B.Tech students and her area interest include Image processing, Computer Graphics and Software Engineering.