Automatic Multiple Visual Inspection on Non-calibrated Image Sequence with Intermediate Classifier Block

Automated inspection using multiple views (AMVI) has been recently developed to automatically detect flaws in manufactured objects. The principal idea of this strategy is that, unlike the noise that appears randomly in images, only the flaws remain stable in a sequence of images because they remain in their position relative to the movement of the object being analyzed. This investigation proposes a new strategy, based on the detection of flaws in a noncalibrated sequence of images. The method uses a scheme of elimination of potential flaws in two and three views. To improve the performance, intermediate blocks are introduced that eliminate those hypothetical flaws that are regular regions and real flaws. Use is made of images captured in a non-calibrated vision system, so there are no optical, geometric and noise disturbances in the image, forcing the proposed method to be robust, so that it can be applied in industry as a quality control method in non-calibrated vision systems. the results show that it is possible to detect the real flaws and at the same time decrease most of the false alarms.