In this study, the red-green-blue (RGB) color values of colored solutions captured from a digital camera are employed for reconstruction of spectral transmission of the transparent solutions. A capturing box is assembled and a spectral data set gathered from colored solutions prepared for this purpose. Principal component analysis (PCA), pseudoinverse, and matrix R methods are employed to reconstruct the spectral transmission of clear solutions from their RGB data. Two different illuminants are employed to achieve two sets of RGB data. According to the results, the PCA method led to inadequate accuracy when a set of RGB data and three eigenvectors are used, while results are improved by using first six basis functions. On the other hand, pseudoinverse leads to the worse results in comparison with PCA by using the first six basis functions. However, the results obtained from matrix R method shows considerable improvement in terms of the root mean square error between the actual and reconstructed spectral transmission curves. In fact, matrix R method diminishes the spectral errors in the two ends of spectrum in relation to other methods.