This work presents na application of Fractal Dimension and Segmentation techniques for Automated Visual Inspection. A System was developed for textile industries that aims automatic failure detection. Such as birch wood board and steel slabs industries, this environment has particular characteristics in which morphological feature extraction can not be used for visual quality control. The System compare data of the digital images. These images data depend on the selected method. Two methods can be used: segmentation or fractal dimension. Segmentation techniques were adapted and improved in order to detect variations of the product s images (signal of defect). The image analysis by the use of fractal dimension is based on a efficient algorithm. This algorithm calculate the fractal dimension images values throughout the range between two and three (2 less than or equal to DF less than or equal to 3). The system have been tested using textile images and the techniques were compared by its efficiency, accuracy and application.