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This paper introduces a computer vision technique for wafer particle metrology and inspection. Artificially generated particle images based on their color properties were used to verify HSV (hue, saturation, value) color space models of each particle and to demonstrate how the proposed method efficiently classifiesparticles by their types with minimum crosstalk. A high-resolution microscope consisting of an imaging system, illumination system, and spectrometer was developed for the experimental validation. The three kinds of micrometer-scale particles were randomly placed on the wafers and the images collected under the exposed white light illumination were analyzed and segmented by particle types based on pre-developed HSV color space models specified for each particle type. The proposed method is expected to inspect and classify various wafer particles in the defect binning process. |
