Oil and gas pipeline operators routinely use magnetic flux leakage (MFL) and ultrasonic (UT) in-line inspection (ILI) to detect, locate and size metal losses caused by corrosion. As a preliminary step in fitness-for-service evaluations, the quality of the ILI is assessed through statistical comparison of the ILI data with data gathered in the field at dig sites. This work presents generalized criteria for the performance assessment and calibration of MFL and UT ILI tools from field measurements. The proposed criteria are capable of accounting for the measurement errors of both the ILI tool and the field instrument. The performance assessment of the ILI run is based on the determination of the minimum number of unsuccessful field verifications required to reject the ILI at a given significance level. The calibration of the ILI data uses new, simplified, error-in-variables methods to estimate the true size of the corrosion metal losses reported by the ILI tool. The proposed methodology also allows for determination of the errors associated with the estimation of the true defect depths. This information is of utmost importance in conducting reliability and risk assessments of pipelines based on either the probability distribution properties of the pipeline defect population, or the probability of failure of each individual defect in the pipeline. The proposed criteria are tested using Monte Carlo simulations and a real-life case study is presented to illustrate their application. © 2007 IOP Publishing Ltd.