Optical member inspection apparatus, image-processing apparatus, image-processing method, and computer readable medium
First Claim
1. An optical member inspection apparatus, comprising:
- an image pick-up device which picks up an image of an inspection target optical member, and outputs image data representing said image of the inspection target optical member;
an extraction processor which extracts, from the image data, a portion of the image having brightness different from other portions of the image, as an extracted object;
a graphic feature value measuring processor which measures a graphic feature value of the extracted object;
a position measuring processor which measures a position of the extracted object in the image data relative to an optical axis of said inspection target optical member;
a normalization processor which normalizes the graphic feature value using a reference based on the position of the extracted object such that the graphic feature value of the extracted object is weighted with a distance between the position of the extracted object and the optical axis of said inspection target optical member so that the graphic feature value becomes heavier as the distance decreases; and
an operation processor which calculates an evaluation function based on all normalized values calculated by the normalization processor for all extracted objects extracted from the image data by the extraction processor.
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Abstract
The image pick-up device picks up an image of the inspection target optical member whenever it rotates a predetermined angle. The image data which is output by the image pick-up device picking-up the image undergoes coordinate transformation from polar coordinate system to rectangular coordinate system and thereafter binarization process. The area of the defective candidate objects which are extracted from the image data in two color system obtained through the binarization process are normalized in accordance with the reference values prepared for each region in which said defective candidate objects formed within the image data. The points which are calculated as a result of this normalization, are added to the corresponding columns in the classification table. It is judged whether the inspection target optical member is satisfactory or not, in accordance with whether or not evaluation function calculated on the basis of the value in each column exceeds a predetermined reference value.
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Citations
26 Claims
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1. An optical member inspection apparatus, comprising:
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an image pick-up device which picks up an image of an inspection target optical member, and outputs image data representing said image of the inspection target optical member;
an extraction processor which extracts, from the image data, a portion of the image having brightness different from other portions of the image, as an extracted object;
a graphic feature value measuring processor which measures a graphic feature value of the extracted object;
a position measuring processor which measures a position of the extracted object in the image data relative to an optical axis of said inspection target optical member;
a normalization processor which normalizes the graphic feature value using a reference based on the position of the extracted object such that the graphic feature value of the extracted object is weighted with a distance between the position of the extracted object and the optical axis of said inspection target optical member so that the graphic feature value becomes heavier as the distance decreases; and
an operation processor which calculates an evaluation function based on all normalized values calculated by the normalization processor for all extracted objects extracted from the image data by the extraction processor. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8)
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9. An optical member inspection apparatus, comprising:
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an image pick-up device which picks up an image of an inspection target optical member, and outputs image data representing said image of the inspection target optical member;
an extraction processor which extracts, from the image data, a portion of the image having brightness different from other portions of the image, as an extracted object;
a graphic feature value measuring processor which measures a graphic feature value of the extracted object;
a position measuring processor which measures a position of the extracted object in the image data;
a normalization processor which normalizes the graphic feature value using a reference based on the position of the extracted object; and
an operation processor which calculates an evaluation function based on all normalized values calculated by the normalization processor for all extracted objects extracted from the image data by the extraction processor, wherein said normalization processor setting the reference higher as a distance between the extracted object and the optical axis of the inspection target optical member increases, wherein said position measuring processor measures the position of the extracted object by discriminating a region from which the extracted object is extracted among a plurality of concentric regions centered on said optical axis, and wherein said normalization processor sets the reference based on the region discriminated by the position measuring processor. - View Dependent Claims (10, 11, 12, 13)
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14. An image-processing apparatus, comprising:
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an extraction processor which extracts, from an image data representing an inspection target optical member, a portion of said image data indicating an extracted object of said optical member having a brightness different from surrounding areas of said optical member;
a graphic feature value measuring processor which measures a graphic feature value of the extracted object;
a position measuring processor which measures a position of the extracted object in the image data relative to an optical axis of said inspection target optical member;
a normalization processor which calculates a normalized value of the extracted object, by normalizing the graphic feature value using a reference based on the position measured by the position measuring processor such that the graphic feature value of the extracted object is weighted with a distance between the position of the extracted object and the optical axis of said inspection target optical member so that the graphic feature value becomes heavier as the distance decreases; and
an operation processor which calculates an evaluation function based on all normalized values calculated by the normalization processor with respect to all extracted objects which are extracted from said image data by the extraction processor.
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15. An image-processing method, comprising:
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extracting, from image data representing an inspection target optical member, an extracted object comprising a portion of said optical member having a brightness different from a surrounding area of said optical member in the image data;
measuring a graphic feature value of the extracted object;
measuring a position of the extracted object in the image data relative to an optical axis of the inspection target optical member;
calculating a normalized value of the extracted object, by normalizing the graphic feature value using a reference in accordance with the position of the extracted object such that the graphic feature value of the extracted object is weighted with a distance between the position of the extracted object and the optical axis of the inspection target optical member so that the graphic feature value becomes heavier as the distance decreases; and
calculating an evaluation function based on all normalized values with respect to all extracted objects which are extracted from said image data. - View Dependent Claims (16, 17, 18, 19, 20)
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21. An image-processing method, comprising:
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extracting, from image data representing an inspection target optical member, an extracted object comprising a portion of an optical member having a brightness different from a surrounding area of the optical member in the image data;
measuring a graphic feature value of the extracted object;
measuring a position of the extracted object in the image data;
calculating a normalized value of the extracted object, by normalizing the graphic feature value using a reference in accordance with the position of the extracted object, the normalized value being calculated by dividing the graphic feature value of the extracted object by the reference which increases as a distance between the extracted object and the optical axis inspection target optical member increases; and
calculating an evaluation function based on all normalized values with respect to all extracted objects which are extracted from the image data, wherein measuring a position of the extracted object discriminates a region, among a plurality of concentric regions within the image of the inspection target optical member about the optical axis of the inspection target optical member, and from which the extracted object is extracted; and
wherein calculating a normalized value divides the graphic feature value of the extracted object by a reference value corresponding to the discriminated region. - View Dependent Claims (22, 23, 24, 25)
calculating, for each of said concentric regions, a total of the normalized values with respect to all extracted objects extracted from each of said concentric regions, respectively; and
calculating a square root of a sum of squares of the totals.
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23. An image-processing method according to claim 21, wherein said calculating an evaluation function comprises:
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classifying the extracted objects in accordance with types of optical defects which can cause the extracted objects;
calculating, for each said concentric region and each said type of optical defect, a total of the normalized values with respect to the extracted object;
calculating, for each said type of optical defect, a square root of a sum of squares of the totals; and
calculating a square root of a sum of the squares of the square roots calculated for each said type of optical defect.
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24. An image-processing method according to claim 23, wherein during said calculating an evaluation function, normalized values less than a predetermined level are discarded, unless at least a predetermined number of other extracted objects are within a predetermined interval from the extracted object having a normalized value less than the predetermined level.
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25. An image-processing method according to claim 23, wherein said calculating an evaluation function further comprises calculating a product of the extracted objects having said normalized value less than the predetermined level with the predetermined interval from one another, the number being larger than the predetermined number, and a constant as the normalized value for all of the extracted objects within the predetermined interval, and classifying a result independently from the other types of optical defects.
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26. A computer readable media storing a program for causing a computer to perform a method, comprising:
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extracting, from image data representing an inspection target optical member, an extricated object portion of said optical member having brightness different from a surrounding area of said optical member;
measuring a graphic feature value of the extracted object relative to an optical axis of said inspection target optical member;
measuring a position of the extracted object in the image data;
calculating a normalized value of the extracted object, by normalizing the graphic feature value using a reference in accordance with the position of the extracted object such that the graphic feature value of the extracted object is weighted with a distance between the position of the extracted object and the optical axis of said inspection target optical member so that the graphic feature value becomes heavier as the distance decreases; and
calculating an evaluation function based on all normalized values with respect to all extracted object which are extracted from same image data.
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Specification