Evaluation of mottle is an area of on-going research in print quality assessment. We propose an unsupervised evaluation technique and a metric that measures mottle in a hard-copy laser print. The proposed algorithm uses a scanned image to quantify the low frequency variation or mottle in what is supposed to be a uniform field. ‘Banding’ and ‘Streaking’ effects are explicitly ignored and the proposed algorithm scales the test targets from “Flat print” (Good) to “Noisy print” (Bad) based on Mottle only. The evaluation procedure is modeled as feature computation in different combinations of spatial, frequency and wavelet domains. The algorithm's results are tested on a dataset of about 23 K only test targets out of which 13 were strictly for performance testing and results representing 10 targets are quantified in the paper against subjective rankings from ∼30 Print Quality Experts (PQE) resulting in a ∼ 91% correlation.