The artificial counting method for solar wafers cannot meet the production requirements because of the inefficiency, high breakage rate and inaccuracy. An accurate counting algorithm for solar wafers based on the texture feature was suggested. Firstly, Texture feature of acquired multilayer solar wafers was analyzed. Secondly, the edges of wafers region were located in the image by the grayscale distribution. Coordinates information of edges were used to correct the image and locate ROI(Region-of-Interest). The thresholding combining NiBlack with background correction was designed to obtain binary image. Noise was removed by particle Filter. The texture feature gap between pieces was improved by morphological method. Finally, counting was realized by self-adaption differential algorithms based on probability statistics. The result of experiments shows that the counting accuracy has achieved to 99.37%. The algorithm mentioned above is not only effective for the wafer images of low contrast, much noise and fuzzy boundaries, but also improves the efficiency and accuracy of the counting.
Bitte loggen Sie sich ein, um Zugang zu diesem Inhalt zu erhalten
Unternehmen haben das Innovationspotenzial der eigenen Mitarbeiter auch außerhalb der F&E-Abteilung erkannt. Viele Initiativen zur Partizipation scheitern in der Praxis jedoch häufig. Lesen Sie hier - basierend auf einer qualitativ-explorativen Expertenstudie - mehr über die wesentlichen Problemfelder der mitarbeiterzentrierten Produktentwicklung und profitieren Sie von konkreten Handlungsempfehlungen aus der Praxis. Jetzt gratis downloaden!