DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries set forth in Graham v. John Deere Co., 383 U.S. 1, 148 USPQ 459 (1966), that are applied for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claims 1-20 are rejected under 35 U.S.C. 103 as being unpatentable over Hiraiet al. (JP 2017003305 A, Defect Image Classification Device), in view of Miyamoto et al. (WO 2012070549 A1, GLOBAL ALIGNMENT USING MULTIPLE ALIGNMENT PATTERN CANDIDATES), hereinafter, “Miyamoto”.
Regarding claim 1, Hiraiet teaches, a controller including circuitry configured to cause the system to perform (Please note, page 7, second paragraph. As indicated a stage controller 112 that controls the stage 106.) obtaining an image of a sample (Please note, page 19, first paragraph. As indicated the MDC processing unit 205 reads the type of the initial display image set for each defect type from the initial display setting information storage unit 211); determining defect characteristics from the image (Please note, page 19, first paragraph. As indicated as a result, the MDC processing unit 205 has an image of the image type associated with the defect type that is the ADC classification result (that is, a part of the plurality of secondary particle detectors 109 associated with the defect type. In this regard, Examiner considers this defect type to correspond to Applicant’s defect characteristics); generating an updated image based on the determined defect characteristics and the image. (Please note, page 19, first paragraph. As indicated the image obtained from the detector (1) is selected as an image to be initially displayed. The type of the initial display image is updated by an initial display image update process (709).).
Hiraiet does not expressly teach, aligning the updated image with a reference image.
Miyamoto teaches, aligning the updated image with a reference image. (Please note, page 23, first paragraph. As indicated the alignment pattern is on the same design data, by obtaining a plurality of OM images, it is possible to know the variation in the appearance of the OM image, and update the appropriateness based on this.).
Hiraiet & Miyamoto are combinable because they are from the same field of endeavor.
At the time before the effective filing date, it would have been obvious to a person of ordinary skill in the art to utilize this aligning the updated image with a reference image of Miyamoto in Hiraiet’s invention.
The suggestion/motivation for doing so would have been as indicated on page 23, first paragraph, “a high degree of appropriateness is set for an alignment pattern candidate in which a part whose appearance changes is outside the template position.”.
Therefore, it would have been obvious to combine Miyamoto with Hiraiet to obtain the invention as specified in claim 1.
Regarding claim 2, Hiraiet teaches, evaluating the image of the sample to identify any one or more defects (Please note, page 23, first paragraph. As indicated identification information 903 for identifying the image type is displayed on the upper left of each defect image.); and determining a set of one or more locations on the image corresponding to the one or more identified defects. (Please note, page 11, first paragraph. As indicated the ADC processing unit 203 executes an automatic defect classification process (ADC process) using the defect image 202 as input information, and automatically classifies the types of defects included in the defect image 202 based on the defect image 202. The defect classification result is stored as an ADC result 204 in the defect information database 121.).
Regarding claim 3, Hiraiet teaches, providing an indication of a set of one or more locations on the updated image that are associated with the set of one or more locations on the image corresponding to the identified one or more defects. defects included in the defect image 202 based on the defect image 202. The defect classification result is stored as an ADC result 204 in the defect information database 121.).
Regarding claim 4, Hiraiet teaches, removing or minimizing the identified one or more defects. (Please note, page 15, first paragraph. As indicated in actual ADR processing, alignment processing between a defect image and a reference image, noise removal processing, synthesis processing of various images, majority processing, threshold processing for luminance values of difference images, and the like are performed.).
Regarding claim 5, Hiraiet teaches, binning the one or more defects based on the indication of the set of one or more locations. (Please note, page 5, second paragraph. As indicated the “defect image classification device” widely includes devices that acquire an image of a sample mainly using a charged particle beam and classify the acquired image according to the type of defect. The “defect image classification system” is a system in which a defect image classification device is connected to other devices via a network or the like, and widely includes systems configured to include a defect image classification device.).
Regarding claim 6, Hiraiet teaches, any one of metadata of the updated image or a characteristic of the updated image. (Please note, page 5, last paragraph. As indicated the “feature amount” is information representing the likelihood of defects. For the feature amount, not only information representing the feature of the detection signal itself obtained from the detection system described below, but also predetermined processing (for example, image processing, calculation processing, statistical processing, etc.) is performed on the detection signal. Information representing the characteristics obtained in this way is also included.).
Regarding claim 7, Hiraiet teaches, adjusting the image to minimize a defect on the image. (Please note, page 25, last paragraph. As indicated the determination of whether to reduce the image type may be set in advance in the defect image classification device 120 or may be specified by the user.).
Regarding claim 8, Hiraiet teaches, wherein the determined defect characteristics comprise intensity levels from the image. (Please note, page 5, last paragraph. As indicated as an example of the feature amount, there is a numerical value of the uneven state, shape, brightness (luminance information) of the defect.).
Regarding claim 9, Hiraiet teaches, wherein the intensity levels from the image correspond to grey levels that indicate voltage contrast. (Please note, page 13, fifth paragraph. As indicated in the SEM type defect observation apparatus having five types of secondary particle detectors, it is easy to recognize in the image 301 of the upper detector, but in the images of the four-direction detector (302, 303, 304, 305). A difficult defect, for example, a defect called a VC (Voltage Contrast) defect will be described as an example.).
Regarding claim 10, Hiraiet teaches, generating the updated image further comprises adjusting the intensity levels at a set of one or more locations on the image corresponding to one or more identified defects to remove or minimize the one or more identified defects. (Please note, page 25, last paragraph. As indicated the determination of whether to reduce the image type may be set in advance in the defect image classification device 120 or may be specified by the user.).
Regarding claim 11, Miyamoto recites, wherein the one or more defects indicate any one of an electrical short or an electrical open. (Please note, page 17, third paragraph. As indicated the matching data 901 to 903 include a square pattern 909 belonging to layer 1 drawn by a solid line, a square pattern 910 belonging to layer 2 drawn by a broken line.).
Regarding claim 12, Miyamoto recites, wherein the one or more defects indicate any one of necking, bridging, edge placement error, hole or a broken line. (Please note, page 13, last paragraph. As indicated the circuit pattern drawn with a solid line is a pattern belonging to layer 1 (for example, the upper layer), and the circuit pattern drawn with a broken line is a pattern belonging to layer 2 (for example, the lower layer).).
Regarding claim 13, Hiraiet teaches, wherein the reference image is based on layout data. (Please note, page 9, last paragraph. As indicated the defect image 202 includes not only the defect image but also a reference image acquired by the ADR processing unit 201, an intermediate image created in the course of the ADR processing, and information such as the validity of each image type in the defect detection processing. May be included.).
Regarding claim 14, Hiraiet teaches, wherein the reference image comprises a golden image. (Please note, page 5, fifth paragraph. As indicated the “reference image” is a standard image used for comparison with a defect image for defect extraction, and represents a normal region, that is, an image of a region estimated to have no defect.).
Regarding claim 15, the analysis are similar to claim 1, as they have similar limitations, except, claim 15, also recites: Hiraiet teaches: mapping the image to a defect-free image (Please note, page 10, second paragraph. As indicated the MDC processing unit 205 displays a defect image 202 on the image display unit 207 for each type of defect based on the ADC result 204. The MDC processing unit 205 prompts the user to confirm the defect image 202 displayed for each defect type (confirmation of the defect image classification result). The user confirms and corrects the defect image classification result on the image display unit 207.); generating an updated image based on the mapping and the image. (Please note, page 10, second paragraph. As indicated when there is no error in the defect image classification result, the user determines the defect image classification result on the screen.).
Regarding claims (16-20), analysis similar to those presented for claims (2-6), respectively, are applicable.
Examiner’s Note
The examiner cites particular figures, paragraphs, columns and line numbers in the references as applied to the claims for the convenience of the applicant. Although the specified citations are representative of the teachings in the art and are applied to the specific limitations within the individual claims, other passages and figures may apply as well.
It is respectfully requested that, in preparing responses, the applicant fully consider the references in their entirety as potentially teaching all or part of the claimed invention, as well as the context of the passage as taught by the prior art or disclosed by the examiner.
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/AMIR ALAVI/Primary Examiner, Art Unit 2668 Saturday, February 21, 2026