Pattern Classification of Fabric Defects Using a Probabilistic Neural Network and Its Hardware Implementation using the Field Programmable Gate Array System
Journal Title: Fibres and Textiles in Eastern Europe - Year 2017, Vol 25, Issue 1
Abstract
This study proposes a fabric defect classification system using a Probabilistic Neural Network (PNN) and its hardware implementation using a Field Programmable Gate Arrays (FPGA) based system. The PNN classifier achieves an accuracy of 98 ± 2% for the test data set, whereas the FPGA based hardware system of the PNN classifier realises about 94±2% testing accuracy. The FPGA system operates as fast as 50.777 MHz, corresponding to a clock period of 19.694 ns.
Authors and Affiliations
Abul Hasnat, Anindya Ghosh, Amina Khatun, Santanu Halder
Keywords
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- EP ID EP199554
- DOI 10.5604/01.3001.0010.1709
- Views 89
- Downloads 0
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