DETAILED DESCRIPTION The foregoing objects are among those achieved by the invention which provides, in one aspect, a machine vision method for inspecting the surfaces of semiconductor dies.
The method includes the steps of generating a first image of the die (including, the patterns etched into its surface and any other structures--together, referred to as the "die," or "die surface" or "background"), generating a second image of the die and any defects thereon, and subtracting the second image from the first image.
The method is characterized in that the second image is generated such that subtraction of it from the first image emphasizes a defect (e.
g.
, excessive adhesive) with respect to the die or background.
In related aspects of the invention, the second step is characterized as generating the second image such that its subtraction from the first image increases a contrast between the defect and the background.
That step is characterized, in still further aspects of the invention, as being one that results in defect-to-background contrast differences in the second image that are of opposite polarity from the defect-to-contrast differences in the first image.
In further aspects, the invention calls for generating a third image with the results of the subtraction, and for isolating the expected defects on that third image.
Isolation can be performed, according to other aspects of the invention, by conventional machine vision segmentation techniques such as connectivity analysis, edge detection and/or tracking, and by thresholding.
In the latter regard, a threshold image--as opposed to one or two threshold values--can be generated by mapping image intensity values of the first or second image.
That threshold image can, then, be subtracted from the third image (i.
e, the difference image) to isolate further the expected defects.
Still further objects of the invention provide for normalizing the first and second images before subtracting them to generate the third image.
In this aspect, the invention determines distributions of intensity values of each of the first and second images, applying mapping functions to one or both of them in order to match the extrema of those distributions
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Image Analysis 
