Asset management is an increasing concern for wastewater utilities and companies. Criteria are developed for supporting the definition of investigation and rehabilitation programs. Dysfunction indicators contribute to the calculation of criteria, using expert rules. These indicators are mostly based on visual inspections, which provide major information. However, difficulties remain in the translation of visual inspection survey into dysfunction indicators. This article presents a methodological approach aiming to fill this lack. In the framework of the French RERAU program (Rehabilitation of urban sewer networks) a methodological approach has been developed in order to convert visual inspections of sewer segments into four possible condition grades {1, 2, 3, 4}, grade 4 corresponds to the worse condition. Three complementary procedures are thus executed: (a) expert rules based on sequences of observation codes, (b) comparison of single score to threshold and (c) rules based on analysis of segment profiles (scores distribution). An experiment lead in the Bas-Rhin (France) illustrates the different steps of the methodological approach and the applicability of the RERAU methodology on CCTV data. Moreover, confrontation between expert assessment of sewer segments (condition grade) and calculated scores has demonstrated the necessity of considering diagnosis imperfection, which may lead to misclassification in some cases. The algorithm proposed in this article aims to minimize a cost function with costs assigned to false positive diagnosis test (segment classified in worse condition than experts' opinion) and false negative diagnosis test (segment classified in better condition than experts' opinion). The algorithm is described in detail and applied to an example. Thus imprecision of assessment is taken into account: the threshold is chosen as to be the most efficient (in term of cost). This approach is generally applicable to numerous domains, when levels of performance need to be defined.