Abstract: Methods and systems for detecting defects on a wafer are provided. One method includes identifying one or more characteristics of first raw output generated for a wafer that correspond to one or more geometrical characteristics of patterned features formed on the wafer and assigning individual output in second raw output generated for the wafer to different segments based on the identified one or more characteristics of the first raw output and based on the individual output in the second raw output and individual output in the first raw output that were generated at substantially the same locations on the wafer such that the one or more geometrical characteristics of the patterned features that correspond to each of the different segments in the second raw output are different.

Abstract: The present invention includes searching imagery data in order to identify one or more patterned regions on a semiconductor wafer, generating one or more virtual Fourier filter (VFF) working areas, acquiring an initial set of imagery data from the VFF working areas, defining VFF training blocks within the identified patterned regions of the VFF working areas utilizing the initial set of imagery data, wherein each VFF training block is defined to encompass a portion of the identified patterned region displaying a selected repeating pattern, calculating an initial spectrum for each VFF training block utilizing the initial set of imagery data from the VFF training blocks, and generating a VFF for each training block by identifying frequencies of the initial spectrum having maxima in the frequency domain, wherein the VFF is configured to null the magnitude of the initial spectrum at the frequencies identified to display spectral maxima.

Abstract: Methods and systems for filtering scratches from wafer inspection results are provided. One method includes generating a defect candidate map that includes image data for potential defect candidates as a function of position on the wafer and removing noise from the defect candidate map to generate a filtered defect candidate map. The method also includes determining one or more characteristics of the potential defect candidates based on portions of the filtered defect candidate map corresponding to the potential defect candidates. In addition, the method includes determining if each of the potential defect candidates are scratches based on the one or more characteristics determined for each of the potential defect candidates and separating the potential defect candidates determined to be the scratches from other defects in inspection results for the wafer.

Abstract: Systems and methods for determining one or more parameters of a wafer inspection process are provided. One method includes aligning optical image(s) of an alignment target to their corresponding electron beam images generated by an electron beam defect review system. The method also includes determining different local coordinate transformations for different subsets of alignment targets based on results of the aligning. In addition, the method includes determining positions of defects in wafer inspection system coordinates based on coordinates of the defects determined by the electron beam defect review system and the different local coordinate transformations corresponding to different groups of the defects into which the defects have been separated. The method further includes determining one or more parameters for an inspection process for the wafer based on defect images acquired at the determined positions by a wafer inspection system.

Abstract: Methods and systems for detecting defects on a wafer using adaptive local thresholding and color filtering are provided. One method includes determining local statistics of pixels in output for a. wafer generated using an inspection system, determining which of the pixels are outliers based on the local statistics, and comparing the outliers to the pixels surrounding the outliers to identify the outliers that do not belong to a cluster of outliers as defect candidates. The method also includes determining a value for a difference in color between the pixels of the defect candidates and the pixels surrounding the defect candidates. The method further includes identifying the defect candidates that have a value for the difference in color greater than or equal to a predetermined value as nuisance defects and the defect candidates that have a value for the difference in color less than the predetermined value as real defects.

Abstract: Methods and systems for detecting defects on a wafer are provided.

Abstract: Methods and systems for detecting defects on a wafer are provided.

Abstract: The present invention includes searching imagery data in order to identify one or more patterned regions on a semiconductor wafer, generating one or more virtual Fourier filter (VFF) working areas, acquiring an initial set of imagery data from the VFF working areas, defining VFF training blocks within the identified patterned regions of the VFF working areas utilizing the initial set of imagery data, wherein each VFF training block is defined to encompass a portion of the identified patterned region displaying a selected repeating pattern, calculating an initial spectrum for each VFF training block utilizing the initial set of imagery data from the VFF training blocks, and generating a VFF for each training block by identifying frequencies of the initial spectrum having maxima in the frequency domain, wherein the VFF is configured to null the magnitude of the initial spectrum at the frequencies identified to display spectral maxima.

Abstract: A processor-based method for detecting defects in an integrated circuit, by creating an image of at least a portion of the integrated circuit with a sensor, grouping pixels of the image into bins based at least in part on a common characteristic of the pixels that are grouped within a given bin, creating a histogram of the pixels in each of the bins, calculating a mean value of the histogram for each of the bins, comparing the mean value for each of the bins to a threshold value, flagging as defect candidates those bins where the mean value of the bin varies from the threshold value by more than a predetermined amount, and performing signature detection on the bins that are flagged as defect candidates, where the image of the integrated circuit is not directly compared to any other image of an integrated circuit.

Abstract: A processor-based method for detecting defects in an integrated circuit, by creating an image of at least a portion of the integrated circuit with a sensor, grouping pixels of the image into bins based at least in part on a common characteristic of the pixels that are grouped within a given bin, creating a histogram of the pixels in each of the bins, calculating a mean value of the histogram for each of the bins, comparing the mean value for each of the bins to a threshold value, flagging as defect candidates those bins where the mean value of the bin varies from the threshold value by more than a predetermined amount, and performing signature detection on the bins that are flagged as defect candidates, where the image of the integrated circuit is not directly compared to any other image of an integrated circuit.