The Black & Scholes formula for theoretical pricing of options exhibits certain systematic biases, asobserved prices in the market differs from the formula. A number of studies attempted to reduce these biasesby incorporating a correction mechanism in the input data. Amongst non-parametric approaches used toimprove accuracy of the model, Artificial Neural Networksare found as a promising alternative. The studymade an attempt to improve accuracy of option price estimation using Artificial Neural Networks where allinput parameters are adjusted by suitable multipliers. The values of these multipliers were determined usingknown data that minimises errors in valuation. The study was carried out using Nifty call option prices quotedon National Stock Exchange for the period 01-Jul 2008 to 30-Jun-11 covering three years.