Finding Ways to Improve the Digital Presentation of Textile Materials for Detecting Defects
The article discusses the possibility of using neural network technologies for the automated search for defects in textile materials. A developed laboratory stand is presented, where samples are photographed to form a training sample. A number of studies have been conducted on the influence of various types of illumination of the material when obtaining an image from the camera. A study was performed on the effect of changing the camera angle relative to the fabric sample. Various options for eliminating the undesirable image distortion are proposed.