Abstract:
There are provided system and method of detecting repeating defects on a specimen, the specimen obtained by printing two or more mask fields thereon, each of mask field comprising multiple dies, the method comprising: scanning the specimen to capture a plurality of first images from first dies located at the same position in the mask fields, and, for each first image, capture two or more second images from dies located in different positions from the first dies; generating a plurality of third images corresponding to the plurality of first images; generating, an average third image constituted by pixels with values computed as accumulated pixel values of corresponding pixels in the plurality of third images divided by the number of the two or more mask fields; and determining presence of repeating defects on the specimen based on the average third image and a predefined defect threshold.
Abstract:
Inspection data that corresponds to potential defects of an object may be received. A first set of locations of first potential defects can be identified. The first set of locations of the first potential defects can be imaged with a review tool to obtain a first set of review images. The first potential defects can be classified based on the first set of review images to obtain first classification results of the first potential defects. A determination can be made as to whether an examination stopping criteria has been satisfied. In response to determining that the examination stopping criteria has not been satisfied, a second set of locations of second potential defects can be identified to be imaged with the review tool to obtain a second set of review images. The second set of locations can be different than the first set of locations.
Abstract:
There are provided system and method of generating an examination recipe usable for examining a specimen, the method comprising: capturing images from dies and obtaining noise map indicative of noise distribution on the images; receiving design data representative of a plurality of design groups each having the same design pattern; calculating a group score for each given design group, the group score calculated based on the noise data associated with the given design group and a defect budget allocated for area of the given design group; providing segmentation related to the dies, comprising: associating design groups with segmentation labels indicative of different noise levels based on the group score, thereby obtaining a set of die segments each corresponding to one or more design groups associated with the same segmentation label and segmentation configuration data; and generating an examination recipe using the segmentation configuration data.
Abstract:
Examination system, method and computer-readable medium, the method comprising: processing by a processor using a first recipe at least one image comprised in images and metadata generated by an inspection tool and stored, to detect a first location set of first potential defects and attributes thereof; selecting and imaging part of the first location set with a review tool to obtain an image set; obtaining classification results of said first potential defects and determining a further recipe based thereon; processing the image using the further recipe for detecting a further location set of further defects; selecting part of the further location set; imaging the part with the review tool to obtain a further image set, and obtaining further classification results; and repeating determining the further recipe, processing the image, selecting and imaging part of the further location set, and obtaining further classification results, until a stopping criteria is met.
Abstract:
There are provided system and method of detecting defects on a specimen, the method comprising: capturing a first image from a first die and obtaining one or more second images; receiving: i) a first set of predefined first descriptors each representing a type of DOI, and ii) a second set of predefined second descriptors each representing a type of noise; generating at least one difference image based on difference between pixel values of the first image and pixel values derived from the second images; generating at least one third image, comprising: computing a value for each given pixel of at least part of the at least one difference image based on the first and second sets of predefined descriptors, and surrounding pixels centered around the given pixel; and determining presence of defect candidates based on the at least one third image and a predefined threshold.
Abstract:
Methods, systems, and computer program products for signature detection. One example of a method includes: acquiring an article defect density map comprising a plurality of sections corresponding to a first resolution level which is indicative of defect numbers for the sections, and determining a distribution representative of the defect numbers or function thereof; determining a threshold in accordance with said distribution, and identifying sections, out of said plurality of sections in the article defect density map, with defect numbers or function thereof above the threshold; and clustering at least part of adjoining identified sections, into one or more signatures, thus detecting said one or more signatures.