Abstract:
A system capable of inspecting an article for defects, the system including: a patch comparator, configured to determine with respect to each of a plurality of reference patches in a reference image a similarity level, based on a predefined patch-similarity criterion and on a source patch defined in the reference image; an evaluation module, configured to rate each inspected pixel out of multiple inspected pixels of the inspection image with a representative score which is based on the similarity level of a reference patch associated with a reference pixel corresponding to the inspected pixel; a selection module, configured to select multiple selected inspected pixels based on the representative scores of the multiple inspected pixels; and a defect detection module, configured to determine a presence of a defect in the candidate pixel based on an inspected value of the candidate pixel and inspected values of the selected inspected pixels.
Abstract:
A defect detection system for computerized detection of defects, the system including: an interface for receiving inspection image data including information of an analyzed pixel and of a plurality of reference pixels; and a processor, including: a differences analysis module, configured to: (a) calculate differences based on an inspected value representative of the analyzed pixel and on multiple reference values, each of which is representative of a reference pixel among the plurality of reference pixels; wherein the differences analysis module is configured to calculate for each of the reference pixels a difference between the reference value of the reference pixel and the inspected value; and (b) compute a representative difference value based on a plurality of the differences; and a defect analysis module, configured to determine a presence of a defect in the analyzed pixel based on the representative difference value.
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.
Abstract:
A system includes a memory and a processor device operatively coupled to the memory to obtain an inspected noise-indicative value representative of an analyzed pixel of an inspected image of an inspected object, and a reference noise-indicative value representative for each of multiple reference pixels of the inspected image. The processor device computes a representative noise-indicative value based on the inspected noise-indicative value and multiple reference noise-indicative values, calculates a defect-indicative value based on an inspected value representative of the analyzed pixel and determines a presence of a defect in the analyzed pixel based on the representative noise-indicative value and the defect-indicative value.
Abstract:
There are provided a method of generating an inspection recipe usable for inspecting an inspection area of a specimen and a recipe generating unit. The recipe generating unit is configured: upon obtaining design data informative of design structural elements comprised in a design PoI corresponding to the at least one PoI, to provide global segmentation of a test image captured by an inspection tool unit from the inspection area and comprising at least one test PoI of substantially the same design as the at least one PoI, thereby to obtain segmented structural elements comprised in the test PoI and segmentation configuration data; to associate the segmented structural elements comprised in the test PoI with the design structural elements comprised in the design PoI, thereby to obtain design association data; and to generate an inspection recipe comprising, at least, segmentation configuration data and design association data.
Abstract:
There are provided a method of inspecting the inspection area and an inspection system thereof. The inspection system comprises an inspection control unit operatively coupled to an inspection tool unit and to a recipe generating unit. The inspection control unit is configured to obtain the design data and the inspection recipe; to provide local segmentation of at least one inspection PoI comprised in an inspection image captured from the inspection area by the inspection tool unit, thereby obtaining inspection structural elements comprised in the at least one inspection PoI, the local segmentation is provided using segmentation configuration data specified in the inspection recipe; to identify one or more target structural elements and design structural elements corresponding thereto, identifying is provided using design association data specified in the inspection recipe; and to enable metrology measurements for the one or more target structural elements using the identified design structural elements.
Abstract:
A system including an interface for receiving inspection image data of an inspection image of an inspection object. The inspection image data includes information of an analyzed pixel of the inspected image and of reference pixels of the inspected image. The system further includes a memory and a processor device operatively coupled to the interface and the memory to obtain an inspected value representative of the analyzed pixel of the inspected image, and a reference value for each of the reference pixels of the inspected image. For each reference pixel, the processor devices calculates a difference between the reference value of a respective reference pixel and the inspected value of the analyzed pixel, computes a representative difference value based on the differences and determines a presence of a defect in the analyzed pixel based on the representative difference value.
Abstract:
There is provided an inspection method capable of classifying defects detected on a production layer of a specimen. The method comprises: obtaining input data related to the detected defects; processing the input data using a decision algorithm associated with the production layer and specifying two or more classification operations and a sequence thereof; and sorting the processed defects in accordance with predefined bins, wherein each bin is associated with at least one classification operation, wherein at least one classification operation sorts at least part of the processed defects to one or more classification bins to yield finally classified defects, and wherein each classification operation, excluding the last one, sorts at least part of the processed defects to be processed by one or more of the following classification operations.
Abstract:
A defect detection system for computerized detection of defects in an inspected object based on processing of an inspection image generated by collecting signals arriving from the inspected object, the system including: an interface for obtaining an inspected noise-indicative value and multiple reference noise-indicative values, the inspected noise-indicative value representative of an analyzed pixel and each of the reference noise-indicative values representative of a reference pixel among a plurality of reference pixels; and a processor, including: a noise analysis module, configured to compute a representative noise-indicative value based on a plurality of noise-indicative values which includes the inspected noise-indicative value and the multiple reference noise-indicative values; and a defect analysis module, configured to calculate a defect-indicative value based on an inspected value representative of the analyzed pixel, and to determine a presence of a defect in the analyzed pixel based on the representative noise-indicative value and the defect-indicative value.