Semiconductor device image inspection with contrast enhancement
AssigneeCognex Corporation
InventorsSanjay J. Nichani, Joseph Scola
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Abstract
Machine vision methods for inspection of semiconductor die lead frames include the steps of generating a first image of the lead frame, generating a second image of the lead frame and any defect thereon, and subtracting the second image from the first image. The methods are characterized in that the second image is generated such that subtraction of it from the first image emphasizes the defect with respect to the lead frame.
Claims17
A machine vision method for inspecting a semiconductor device, including either a semiconductor die lead frame or a semiconductor surface, comprising the steps of:
- illuminating the semiconductor device with an illumination source selected from a group of illumination sources including a direct on-axis light source and a diffuse off-axis light source, wherein the on-axis and off-axis sources are each selected and positioned to provide an image of the semiconductor device having a defect-to-background contrast polarity which is opposite to that of the other source;
- generating a first on-axis image of the semiconductor device with an image capture device while it is so illuminated;
- illuminating the semiconductor device with another illumination source selected from the aforesaid group;
- generating a second on-axis image of the semiconductor device with the image capture device while it is so illuminated;
- and
- subtracting the second image from the first image to form a third image that emphasizes any defect on the semiconductor device.
A method according to 1, wherein the normalizing step includes the steps of
- determining distributions of intensity values of each of the first and second images;
- generating a mapping function for matching extrema of those distributions;
- and
- transforming the intensity values of at least one of the first and second images with that mapping function.
A machine vision method for inspecting a semiconductor device, including either a semiconductor die lead frame or a semiconductor surface, comprising the steps of:
- illuminating the semiconductor device with an illumination source selected from a group of illumination sources including a direct on-axis light source and a diffuse off-axis light source, wherein the on-axis and off-axis sources are each selected and positioned to prove an image of the semiconductor device having a defect-to-background contrast polarity which is opposite to that of the other source;
- generating a first on-axis image of the semiconductor device with an image capture device while it is so illuminated;
- illuminating the semiconductor device with another illumination source selected from the aforesaid group;
- generating a second on-axis image of the semiconductor device with the image capture device while it is so illuminated;
- subtracting the second image from the first image to form a third image that emphasizes any defect on the semiconductor device;
- and
- isolating the defect in the third image by any of segmentation, edge detection and tracking, connectivity analysis, and thresholding.
A machine vision method for inspecting a semiconductor device, including either a semiconductor die lead frame or a semiconductor surface, comprising the steps of
- illuminating the semiconductor device with an illumination source selected from a group of illumination sources including a direct on-axis light source and a diffuse off-axis light source;
- generating a first on-axis image of the semiconductor device with an image capture device while it is so illuminated;
- illuminating the semiconductor device with another illumination source selected from the aforesaid group;
- generating a second on-axis image of the semiconductor device with the image capture device while it is so illuminated;
- subtracting the second image from the first image to form a third image that emphasizes any defect on the semiconductor device;
- isolating the defect from the third image, said isolating step comprising the step of thresholding the third image to distinguish at least one of a defect and its edges from the semiconductor device;
- generating a threshold image from at least one of the first and second images, the threshold image having pixels representing local threshold intensity values;
- and
- using the threshold image to distinguish, the third image, at least one of the defect and its edges from the semiconductor device.
Dependencies are inferred from the claim text.