Banknotes are monetary standards utilized by any country to complete money related exercises and are each nation resource which each country needs it (certified receipt) to be real. A few reprobates present phony notes which look somewhat like unique note to make disparities of the cash in the money related market. It is troublesome for people to tell genuine and counterfeit banknotes separated particularly on the grounds that they have a great deal of comparative highlights. This paper proposes PCA and LDA techniques are utilized for dimensionality decrease and Back proliferation Neural Network (BPNN) classifier is utilized for confirmation of banknotes. Banknotes highlights are extricated dependent on primary segment examination (PCA) and straight discriminant investigation (LDA). PCA productively diminishes measurement of face pictures and speak to them with eigenfaces; while LDA is on the other hand used to enhance discriminant capacity of the PCA calculation. The principles given by BPNN are likewise tried and discovered that they are sufficiently exact to be utilized for banknotes expectation.
