Applied Materials Israel Limited

Harsa Studio Ltd.

Applied Materials, Inc.

Addis Housewares Limited

Yehuda Cohen

Efrat Rozenman

Moshe Amzaleg

Rafael Bistritzer

Refael Minyan

Evgeni Levin

Nir Ben-David Dodzin

Nir Ben-David Dodzen

Gadi Greenberg

Doron Meshulach

Shimon Levi

Efrat Rosenman

Kobi Kan

Erez Ravid

Martyn Lee-Smith

Jeong Ho Yeo

Martin Lee - Smith

There is provided a method and a system configured to compensate for image distortions. An example method includes first receiving a warped image of an array of cells of a specimen. Each cell of the array comprises one or more structural elements of a substrate. A reference image of a region associated with a cell of the array of cells is generated and a first cell of the array of cells is identified using the reference image and at least part of the warped image. One or more locations comprising cells that differ from the first cell are identified and, based at least on the one or more locations, a warped compensation transform is determined. The warped compensation transform is applied on the warped image to generate an undistorted image.

Reconstruction of a distorted image of an array of structural elements of a specimen

There is provided a method and a system configured obtain an image of a semiconductor specimen including one or more arrays, each including repetitive structural elements, and one or more regions, each region at least partially surrounding a corresponding array and including features different from the repetitive structural elements, wherein the PMC is configured to, during run-time scanning of the semiconductor specimen, perform a correlation analysis between pixel intensity of the image and pixel intensity of a reference image informative of at least one of the repetitive structural elements, to obtain a correlation matrix, use the correlation matrix to distinguish between one or more first areas of the image corresponding to the one or more arrays and one or more second areas of the image corresponding the one or more regions, and output data informative of the one or more first areas of the image.

Identification of an array in a semiconductor specimen

Foldable laundry basket

A foldable laundry hamper having a folded and unfolded state, and in the folded state a floor panel and a cover of the hamper are sandwiched between the front and back panels and the hamper occupies a relatively small volume.

EZE-pack laundry hamper

There is provided a method and a system configured to compensate for image distortions.

Laundry basket

A reconfigurable container is disclosed, the container being reconfigurable between a first configuration in which the container defines a receptacle for receiving an item, and a second configuration in which the container comprises a collapsed configuration for storage. The container comprises: a base and a wall which is arranged to extend around the base, the wall comprising at least two hingedly coupled wall portions, the base being hingedly coupled to a lower region of at least one wall portion, the wall further comprising a ledge disposed along a lower region thereof which is arranged to extend inwardly of the container, for supporting the base when the container is configured in the first configuration.

Reconfigurable container

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.

System, method and computer program product for defect detection based on multiple references

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.

Method, system, and computer program product for detection of defects based on multiple references

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.

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.

A method for characterizing a surface of a sample object, the method including dividing the surface into pixels which are characterized by a parameter variation, and defining blocks of the surface as respective groups of the pixels. The method further includes irradiating the pixels in multiple scans over the surface with radiation having different, respective types of polarization, and detecting returning radiation from the pixels in response to each of the scans. For each scan, respective block signatures of the blocks are constructed, in response to the returning radiation from the group of pixels in each block. Also for each scan, a block signature variation using the respective block signatures of the blocks is determined. In response to the block signature variation, one or more of the types of polarization for use in subsequent examination of a test object are selected.

High throughput across-wafer-variation mapping

A method for inspecting a substrate for defects, including: (a) obtaining an inspected pixel and a reference pixel; (b) calculating an inspected value and a reference value, the inspected value representative of the inspected pixel and the reference value representative of the reference pixel; (c) selecting a threshold in response to a selected value out of the inspected value and the reference value; and (d) determining a relationship between the selected threshold, the reference value and the inspected value to indicate a presence of a defect.

Growing community of inventors

Moshav Timorim, Israel

Yehuda Cohen