DEFECT IMAGE CLASSIFICATION DEVICE AND DEFECT IMAGE CLASSIFICATION METHOD
In a defect classification operation in which ADC and visual classification are both used, a problem with the visual classification in the related art is solved, and then the high-reliability performance evaluation of the ADC and the update of the ADC learning data set are made possible, using both the ADC and the visual classification, or both the ADC and one other classification apparatus. An apparatus that classifies defect images is configured to include: a storage unit in which the defect images that are obtained by being captured with separate image capture means are stored; an image selection unit that selects images from among the defect images that are stored in the storage unit, using information on defect classes into which defects are classified in a plurality of separate defect classification means; an image classification unit that classifies the images which are selected in the image selection unit, based on a classification recipe; a classification performance evaluation unit that evaluates classification performance of the image classification unit based on a result of the classification of the images; and a learning update unit that updates the classification recipe of the image classification unit using the images that are selected in the image selection unit in a case where the result of the evaluation in the classification performance evaluation unit does not satisfy a reference that is in advance set.
1 . A defect image classification apparatus that classifies defect images, comprising:
a storage unit in which the defect images that are obtained by being captured in separate image capture means are stored;
an image selection unit that selects images from among the defect images that are stored in the storage unit, using information on defect classes into which defects are classified in a plurality of separate defect classification means;
an image classification unit that classifies the images which are selected in the image selection unit, based on a classification recipe;
a classification performance evaluation unit that evaluates classification performance of the image classification unit based on a result of the classification of the images; and
a learning update unit that updates the classification recipe of the image classification unit using the images that are selected in the image selection unit in a case where the result of the evaluation in the classification performance evaluation unit does not satisfy a reference that is in advance set.
2 . The defect image classification apparatus that classifies defect images according to claim 1 , further comprising:
a defect class comparison unit that compares defect classes that result from the classification in the plurality of separate defect classification means,
wherein the images are selected in the image selection unit from among the defect images that are stored in the storage unit, based on information that results from the comparison in the defect class comparison unit.
3 . The defect image classification apparatus that classifies defect images according to claim 1 ,
wherein the learning update unit updates the classification recipe of the image classification unit using a defect image that is determined as an unknown defect class in the image classification unit, among the images that are selected in the image selection unit, in a case where the result of the evaluation in the classification performance evaluation unit does not satisfy the reference that is in advance set.
4 . The defect image classification apparatus that classifies defect images according to claim 1 ,
wherein the image classification unit classifies the defect images that are obtained by being captured in the separate image capture means, which are stored in the storage unit, based on the classification recipe, and
wherein, in a case where the number of defects that are determined as an unknown defect class as a result of the classification in the image classification unit is equal to or greater than a number that is in advance set, the image selection unit selects an image from among the defect images that are stored in the storage unit, using the information on the defect classes into which the defects are classified in the plurality of separate defect classification means.
5 . The defect image classification apparatus that classifies defect images according to claim 1 ,
wherein the separate image capture means and the plurality of separate defect classification means are connected to each other through a communication line.
6 . A defect image classification apparatus that classifies defect images, comprising:
a storage unit in which the defect images that are obtained by being captured in separate image capture means are stored;
an image selection unit that selects images from among the defect images that are stored in the storage unit, using information on defect classes into which defects are classified in a plurality of separate defect classification means;
an image classification unit that classifies the images which are stored in the storage unit, based on a classification recipe; and
a learning update unit that updates the classification recipe of the image classification unit using the images that are selected in the image selection unit.
7 . The defect image classification apparatus that classifies defect images according to claim 6 , further comprising:
a defect class comparison unit that compares defect classes that result from the classification in the plurality of separate defect classification means,
wherein the images are selected in the image selection unit from among the defect images that are stored in the storage unit, based on information that results from the comparison in the defect class comparison unit.
8 . The defect image classification apparatus that classifies defect images according to claim 6 ,
wherein the learning update unit updates the classification recipe of the image classification unit using a defect image that is determined as an unknown defect class in the image classification unit, among the images that are selected in the image selection unit, in a case where the result of the evaluation in the classification performance evaluation unit does not satisfy the reference that is in advance set.
9 . The defect image classification apparatus that classifies defect images according to claim 6 ,
wherein the image classification unit classifies the defect images that are obtained by being captured in the separate image capture means, which are stored in the storage unit, based on the classification recipe, and
wherein, in a case where the number of defects that are determined as an unknown defect class as a result of the classification in the image classification unit is equal to or greater than a number that is in advance set, the image selection unit selects an image from among the defect images that are stored in the storage unit, using the information on the defect classes into which the defects are classified in the plurality of separate defect classification means.
10 . The defect image classification apparatus that classifies defect images according to claim 6 ,
wherein the separate image capture means and the plurality of separate defect classification means are connected to each other through a communication line.
11 . A defect image classification method of classifying defect images, comprising:
storing the defect images that are obtained by being captured in separate image capture means, in a storage unit;
selecting images in an image selection unit from among the defect images that are stored in the storage unit, using information on defect classes into which defects are classified in a plurality of separate defect classification means;
classifying the images which are selected in the image selection unit, in an image classification unit, based on a classification recipe;
evaluating classification performance of the image classification unit, in a classification performance evaluation unit, based on a result of the classification of the images; and
updating the classification recipe of the image classification unit, in a learning update unit, using the images that are selected in the image selection unit in a case where the result of the evaluation in the classification performance evaluation unit does not satisfy a reference that is in advance set.
12 . The defect image classification method of classifying defect images according to claim 11 , further comprising:
a process of comparing defect classes that result from the classification in the plurality of separate defect classification means, in a defect class comparison unit,
wherein the images are selected in the image selection unit from among the defect images that are stored in the storage unit, based on information that results from the comparison in the defect class comparison unit.
13 . The defect image classification method of classifying defect images according to claim 11 ,
wherein the updating of the classification recipe that is performed in the learning update unit includes updating the classification recipe of the image classification unit, using a defect image that is determined as an unknown defect class in the image classification unit, among the images that are selected in the image selection unit, in a case where the result of the evaluation in the classification performance evaluation unit does not satisfy the reference that is in advance set.
14 . The defect image classification method of classifying defect images according to claim 11 ,
wherein the defect images that are obtained by being captured in the separate image capture means, which are stored in the storage unit, are classified in the image classification unit, based on the classification recipe, and
wherein, in a case where the number of defects that are determined as an unknown defect class as a result of the classification in the image classification unit is equal to or greater than a number that is in advance set, an image from among the defect images that are stored in the storage unit is selected in the image selection unit, using the information on the defect classes into which the defects are classified in the plurality of separate defect classification means.
15 . The defect image classification method of classifying defect images according to claim 11 ,
wherein information from each of the separate image capture means and the plurality of separate defect classification means is acquired through a communication line.
16 . A defect image classification method of classifying defect images, comprising:
storing the defect images that are obtained by being captured with separate image capture means, in a storage unit;
selecting images in an image selection unit from among the defect images that are stored in the storage unit, using information on defect classes into which defects are classified in a plurality of separate defect classification means;
classifying the images which are stored in the storage unit, in an image classification unit, based on a classification recipe; and
updating the classification recipe of the image classification unit in a learning update unit, using the images that are selected in the image selection unit.
17 . The defect image classification method of classifying defect images according to claim 16 , further comprising:
a process of comparing defect classes that result from the classification in the plurality of separate defect classification means, in a defect class comparison unit,
wherein the images are selected in the image selection unit from among the defect images that are stored in the storage unit, based on information that results from the comparison in the defect class comparison unit.
18 . The defect image classification method of classifying defect images according to claim 16 ,
wherein the updating of the classification recipe that is performed in the learning update unit includes updating the classification recipe of the image classification unit, using a defect image that is determined as an unknown defect class in the image classification unit, among the images that are selected in the image selection unit, in a case where the result of the evaluation in the classification performance evaluation unit does not satisfy the reference that is in advance set.
19 . The defect image classification method of classifying defect images according to claim 16 ,
wherein the defect images that are obtained by being captured in the separate image capture means, which are stored in the storage unit, are classified in the image classification unit, based on the classification recipe, and
wherein, in a case where the number of defects that are determined as an unknown defect class as a result of the classification in the image classification unit is equal to or greater than a number that is in advance set, an image from among the defect images that are stored in the storage unit is selected in the image selection unit, using the information on the defect classes into which the defects are classified in the plurality of separate defect classification means.
20 . The defect image classification method of classifying defect images according to claim 16 ,
wherein information from each of the separate image capture means and the plurality of separate defect classification means is acquired through a communication line.