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BISM24: Automating Defect Detection for Blind Textile Workers

Project Description:

BISM24 created real-time automated defect detection for blind textile workers at the Blind Industries & Services of Maryland (BISM) Salisbury MD facility. The system removes the reliance on sighted inspectors to find errors in the textiles before they reach the sewing stage at the factory. A neural network, trained by the team on a matrix of defects and material types, detects issues within 23milliseconds and reports to blind operators or remote operators via web interface. The device is currently in place and operating in the factory. This project is a fantastic example of advanced image processing and neural networks as assistive technology for the disabled community.

Project Photo:

The BISM24 system alerts blind operators to defects in fabric on a spreading machine at the BISM factory in Salisbury Maryland.

The BISM24 system alerts blind operators to defects in fabric on a spreading machine at the BISM factory in Salisbury Maryland.

Student Team Members

  • Ray Chen
  • Jay Lawrence
  • Harrison Le
  • Amy Zhang

Course Faculty

  • Rich Bauernschub
  • Dr. Stephen Belkoff

Project Mentors, Sponsors, and Partners