Polycrystalline Silicon Wafer Surface Color Defect Inspection Based on Machine Vision

Abstract

As non-uniform color and complex texture exist on the polycrystalline silicon solar cell, manual surface inspection adopted by most domestic factories suffers from low efficiency and poor repetitive detection ability. To overcome the shortcomings of manual inspection, based on machine vision and SVM, an automatic silicon wafer surface defect detection and classification system has been developed in this paper: through feature extraction of color images and defect areas, a series of wafer classifiers are trained and used to separate the defective products from qualified ones. Experiments on samples and actual application in the enterprise show that the system has achieved high accuracy and fast run-time performance, indicating that machine vision is an effective and promising method for polycrystalline silicon solar cell inspection.