Antonella Branca, Maria Tafuri, Giovanni Attolico, Arcangelo Distante
Optical Engineering, Vol. 35, Issue 12, (December 1996) https://doi.org/10.1117/1.601111
TOPICS: Inspection, Neural networks, Classification systems, Image classification, Optical engineering, Coherence (optics), Defect detection, Image segmentation, Visualization, Manufacturing
A leather inspection system based on visual textural properties of the material surface is presented. Defects are isolated from the complex and nonhomogeneous background, analyzing their oriented structure. The patterns to be analyzed are represented in an appropriate parameter space using a neural network, in this way, a parameter vector is associated to each different textured region in the original image. Finally a filter process, based on knowledge about the parameter vectors representing the leather without defects, detects and classifies any abnormality. The resulting system is flexible and does not depend on dimensions, structure, and color of defects.