  This paper introduces a new type of system for fabric defect detection with
the tactile inspection system. Different from existed visual inspection
systems, the proposed system implements a vision-based tactile sensor. The
tactile sensor, which mainly consists of a camera, four LEDs, and an elastic
sensing layer, captures detailed information about fabric surface structure and
ignores the color and pattern. Thus, the ambiguity between a defect and image
background related to fabric color and pattern is avoided. To utilize the
tactile sensor for fabric inspection, we employ intensity adjustment for image
preprocessing, Residual Network with ensemble learning for detecting defects,
and uniformity measurement for selecting ideal dataset for model training. An
experiment is conducted to verify the performance of the proposed tactile
system. The experimental results have demonstrated the feasibility of the
proposed system, which performs well in detecting structural defects for
various types of fabrics. In addition, the system does not require external
light sources, which skips the process of setting up and tuning a lighting
environment.
