This paper presents an automated system for quality control of fabrics. It is based on a linear vision machine designed to be integrated on to weavers. The aim is to detect and identify, in real time, faults in the fabric in order to perform on-line diagnosis of the weavers. A solution based on a high-resolution linear multisensor device is proposed in order to cope with the small size of the flaws which occur on wide fabrics. A front processor integrated on the acquisition board performs local operations on the successive line images as they are captured by the multisensor device. Flaws are discriminated using a set of local detection operators and adaptive models. These models are used to extrapolate the image of the fabric, so that any flaw can be detected by comparing the actual image to this theoretical model. The detected flaws are identified by means of morphological filtering and a syntactic classification scheme that discriminates the flaws.