US5774573A
Expired / Lapsed
US
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Automatic visual inspection system
Assignee: Orbotech Ltd
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Filing: 1995-03-17
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Granted: 1998-06-30
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Expires: 2015-03-17
Abstract
Abstract A binary map of an object having edges is produced by first producing a digital grey scale image of the object with a given resolution, and processing the grey scale image to produce a binary map of the object at a resolution greater than said given resolution. Processing of the grey scale image includes the step of convolving the 2-dimensional digital grey scale image with a filter function related to the second derivative of a Gaussian function forming a 2-dimensional convolved image having signed values. The location of an edge in the object is achieved by finding zero crossings between adjacent oppositely signed values. Preferably, the zero crossings are achieved by an interpolation process that produces a binary bit map of the object at a resolution greater than the resolution of the grey scale image. The nature of the Gaussian function whose second derivative is used in the convolution with the grey scale image, namely its standard deviation, is empirically selected in accordance with system noise and the pattern of the traces on the printed circuit board such that the resulting bit map conforms as closely as desired to the lines on the printed circuit board. The convolution can be performed with a difference-of-two-Gaussians, one positive and one negative. It may be achieved by carrying out a one-dimensional convolution of successive lines of the grey scale image to form a one-dimensional convolved image, and then carrying out an orthogonal one-dimensional convolution of successive lines of the one-dimensional convolved image to form a two-dimensional convolved image. Each one-dimensional convolved image may be formed by multiple convolutions with a boxcar function.
Inventors
- 👤 Amiran Caspi
- 👤 Zeev Smilansky
Bibliographic Details
Application Number
—
Jurisdiction
US
Data Source
google_patents
Last Synchronized
2026-11-09 13:43
CPC Classifications
G; G06; G06T; G06T7/00; G06T7/0002; G06T7/0004; G06T3/00; G06T3/40; G06T3/403; G06T7/10; G06T7/12; G06T2200/00; G06T2200/28; G06T2207/00; G06T2207/30; G06T2207/30108; G06T2207/30141
Claims Analysis
Total Claims: 19
Claim 1
Independent Claim
128 words
A process for producing a binary map of an object having a surface each elemental area of which has one or the other of two properties, said process comprising: a) scanning said surface to obtain data representative of a grey scale image of said surface with a given resolution; b) processing said data representative of said grey scale image to produce data representative of a map of said object having signed values that identify adjacent elemental areas of said surface having different properties, said map having the same resolution as said grey scale image; and c) converting said data representative of a map of said object having signed values to a binary map of said surface with a resolution higher than the resolution of said grey scale image.
Claim 2
Dependent Claim
128 words
A process for producing a binary map of an object having a surface each elemental area of which has one or the other of two properties, said process comprising: a) scanning said surface to obtain data representative of a grey scale image of said surface with a given resolution; b) processing said data representative of said grey scale image to produce data representative of a map of said object having signed values that identify adjacent elemental areas of said surface having different properties, said map having the same resolution as said grey scale image; and c) converting said data representative of a map of said object having signed values to a binary map of said surface with a resolution higher than the resolution of said grey scale image.
Claim 3
Dependent Claim
44 words
A process according to claim 1 wherein data representative of the properties of said surface are obtained during the scanning of said surface, and are utilized during the process of converting said data representative of a map of said object to said binary map.
Claim 4
Dependent Claim
25 words
A process according to claim 2 wherein processing said data includes convolving with a filter function that approximates the second derivative of a Gaussian function.
Claim 5
Dependent Claim
35 words
A process according to claim 2 wherein said data representative of the properties of said surface are obtained by comparing the data representative of a grey scale image of said surface with a calibration function.
Claim 6
Dependent Claim
21 words
A process according to claim 4 wherein the calibration function is independent of the location of elemental areas of said surface.
Claim 7
Dependent Claim
14 words
A process according to claim 4 wherein the calibration function is a fixed threshold.
Claim 8
Dependent Claim
14 words
A process according to claim 4 wherein the calibration function is a variable threshold.
Claim 9
Dependent Claim
22 words
A process according to claim 4 wherein the calibration function is dependent on the grey scale levels of the grey scale image.
Claim 10
Dependent Claim
44 words
A process according to claim 8 wherein the data representative of the properties of said surface involve a comparison of the grey level of a pixel in the grey scale image with the grey levels of adjacent neighboring pixels in said grey scale image.
Claim 11
Dependent Claim
21 words
A process according to claim 8 wherein a plurality of adjacent neighboring pixels to each pixel are involved in said comparison.
Claim 12
Dependent Claim
52 words
A process according to claim 10 wherein said comparison is achieved by determining the maximum difference between the grey scale level of the particular pixel and the grey scale levels of neighboring pixels, and averaging the grey scale levels of the particular pixel and the neighboring pixel that produces the maximum difference.
Claim 13
Dependent Claim
17 words
A process according to claim 4 wherein said calibration function is obtained by an off-line calibration process.
Claim 14
Dependent Claim
68 words
A process according to claim i wherein the process of converting data to said binary map includes assigning states to those binary map pixels whose states are capable of being classified unambiguously, including those binary map pixels that are homologous to elemental areas of said surface identified in step (b) of claim 1, and assigning states to the remainder of the binary map pixels according to pre-set rules.
Claim 15
Dependent Claim
41 words
A process according to claim 13 including computing an ordered pair of numbers for each pixel in the grey scale image, and assigning a tentative state to each pixel in accordance with a threshold function obtained by an off-line calibration process.
Claim 16
Dependent Claim
170 words
A process for producing a binary map of an object having a surface each elemental area of which has one or the other of two properties, said process comprising: a) scanning said surface to obtain data representative of a grey scale image of said surface with a given resolution; b) convolving said data representative of said grey scale image to produce a convolution map of said object having signed values; c) producing from said data representative of said grey scale image, a binary gradient-enable map for identifying pairs of contour pixels which are pixels homologous to elemental areas of said surface having different properties, and a binary adjacency map for identifying pixels whose neighboring pixels have a grey level gradient exceeding a threshold; and d) using said gradient-enable map and said adjacency map to create a binary of said surface with said given resolution; and e) interpolating said binary map to form a binary map of said object with a resolution higher than the resolution of said grey scale image.
Claim 17
Dependent Claim
170 words
A process for producing a binary map of an object having a surface each elemental area of which has one or the other of two properties, said process comprising: a) scanning said surface to obtain data representative of a grey scale image of said surface with a given resolution; b) convolving said data representative of said grey scale image to produce a convolution map of said object having signed values; c) producing from said data representative of said grey scale image, a binary gradient-enable map for identifying pairs of contour pixels which are pixels homologous to elemental areas of said surface having different properties, and a binary adjacency map for identifying pixels whose neighboring pixels have a grey level gradient exceeding a threshold; and d) using said gradient-enable map and said adjacency map to create a binary of said surface with said given resolution; and e) interpolating said binary map to form a binary map of said object with a resolution higher than the resolution of said grey scale image.
Claim 18
Dependent Claim
225 words
A process for off-line production of a threshold function comprising: a) scanning an object having a surface each elemental area of which has one or the other of two properties to obtain data representative of a grey scale image of said surface; b) processing said grey scale image to obtain data representative of a binary image in which pixels homologous to elemental areas of said surface at which transitions of said properties occur have a given state and the remaining pixels have the opposite state; c) convolving said data representative of said grey scale image to produce a convolution score image in which the value of each pixel is dependent on the value of its eight neighbors as determined by a look-up table; d) identify contours in said convolution score image; e) classify each contour as being good, bad, or unsure; f) calculate for each pixel in the grey scale image, an ordered pair of numbers; g) plot the ordered pair of numbers for each contour pixel that in not classified as being unsure; h) compute a threshold function from the plotted ordered pairs of numbers as a function that minimizes both the number of points associated with pixels from good contours that are below the threshold function, and the number of points associated with pixels from bad contours that are above the threshold function.
Claim 19
Dependent Claim
225 words
A process for off-line production of a threshold function comprising: a) scanning an object having a surface each elemental area of which has one or the other of two properties to obtain data representative of a grey scale image of said surface; b) processing said grey scale image to obtain data representative of a binary image in which pixels homologous to elemental areas of said surface at which transitions of said properties occur have a given state and the remaining pixels have the opposite state; c) convolving said data representative of said grey scale image to produce a convolution score image in which the value of each pixel is dependent on the value of its eight neighbors as determined by a look-up table; d) identify contours in said convolution score image; e) classify each contour as being good, bad, or unsure; f) calculate for each pixel in the grey scale image, an ordered pair of numbers; g) plot the ordered pair of numbers for each contour pixel that in not classified as being unsure; h) compute a threshold function from the plotted ordered pairs of numbers as a function that minimizes both the number of points associated with pixels from good contours that are below the threshold function, and the number of points associated with pixels from bad contours that are above the threshold function.
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USPTO Annuity & Maintenance Windows
| Annuity Stage | Window Opens | Payment Deadline | Surcharge Period Until | Estimated Fee | Status |
|---|---|---|---|---|---|
| 3.5 Years (Year 4) | 2001-06-29 | 2001-12-29 | 2002-06-30 | $2000.00 | Window Closed / Lapsed |
| 7.5 Years (Year 8) | 2005-06-29 | 2005-12-29 | 2006-06-30 | $3760.00 | Window Closed / Lapsed |
| 11.5 Years (Year 12) | 2009-06-29 | 2009-12-29 | 2010-06-30 | $7700.00 | Window Closed / Lapsed |