Manipulation of Camera Sensor Data via Fault Injection for Anomaly\n Detection Studies in Verification and Validation Activities For AI

Abstract

In this study, the creation of a database consisting of images obtained as a\nresult of deformation in the images recorded by these cameras by injecting\nfaults into the robot camera nodes and alternative uses of this database are\nexplained. The study is based on an existing camera fault injection software\nthat injects faults into the cameras of a working robot and collects the normal\nand faulty images recorded during this injection. The database obtained in the\nstudy is a source for the detection of anomalies that may occur in robotic\nsystems. Within the scope of this study, a database of 10000 images consisting\nof 5000 normal and 5000 faulty images was created. Faulty images were obtained\nby injecting seven different types of image faults, namely erosion, dilation,\nopening, closing, gradient, motionblur and partialloss, at different times\nwhile the robot was operating.\n