DETAILED ACTION
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Claims 1, 4-12 and 14-17 are pending.
Claims 2, 3 and 13 are canceled.
Claim Rejections - 35 USC § 103
The following is a quotation of pre-AIA 35 U.S.C. 103(a) which forms the basis for all obviousness rejections set forth in this Office action:
(a) A patent may not be obtained though the invention is not identically disclosed or described as set forth in section 102 of this title, if the differences between the subject matter sought to be patented and the prior art are such that the subject matter as a whole would have been obvious at the time the invention was made to a person having ordinary skill in the art to which said subject matter pertains. Patentability shall not be negatived by the manner in which the invention was made.
Claim(s) 1, 11-12 and 14-17 is/are rejected under 35 U.S.C. 103 as being unpatentable over Matsuda (US20210302155A1) in view of and further in view of Jun et al (US20040086167A1).
Regarding claims 1, 11 and 12, Subrahmanyan teaches a profile detection method, comprising:
region detecting, by analyzing data of an image of a cross section of a substrate in which a plurality of files are deposited in one direction and a plurality of recesses recessed in the one direction are arranged in an intersecting direction with respect to the one direction of the plurality of films, each recess region in the image;
(Matsuda, "an image of a cross section of a sample to be processed is obtained by scanning electron microscope (SEM) or transmission electron microscope (TEM)", [0003]; "specifies a target region in the input image by using the ROI detection algorithm", [0069]; "(3) L3: height of the mask 608, (4) L4: depth of the trench 609.", [0093]; region detecting by analyzing data of a cross-sectional image of a sample/substrate)
boundary detecting a boundary of the plurality of films included in the image by analyzing the data; and
(Matsuda, "coordinates of a boundary line between the processed structure and the background or a boundary line of an interface between different materials in the image", [0049]; "(1) L1: width of an interface between mask and substrate 606", [0093]; boundary detecting by calculating and identifying the boundary lines and interfaces between different deposited materials or films in the image data)
contour detecting a contour of the recess for the each recess region in the image by analyzing the data,
(Matsuda, "a method for extracting an outline of an object by recognizing a region of each individual object reflected in an image", [0016]; "detects a region of interest (ROI) by using a ROI detection algorithm on a given input image, and estimates a color-coded image for each region by using the trained semantic segmentation model on the detected ROI.", [0051]; contour detecting by recognizing and extracting the outline of specific individual objects or regions, which would include the detected trench/recess regions, using image data analysis)
Matsuda does not expressly disclose but Jun teaches:
wherein the region detecting includes a frequency analysis that performed on the image in the intersecting direction at each position in the one direction of the image, a range in which frequencies corresponding to the plurality of recesses are obtained is specified as a range of the image including the plurality of recesses with respect to the one direction, and the each recess region is detected from the specified range of the image.
(Jun; "periodic pattern such as a line shaped pattern including constant intervals, or a pattern having periodic recesses.", [0026]; "The FFT method can be achieved in two dimensions since the FFT method is performed concerning the space domain like the region to be analyzed. Namely, the FFT method is executed concerning the region in an X-axis direction and a Y-axis direction.", [0027]; "gray levels that are obtained by the Fast Fourier Transformation method using images respectively generated from the pixels positioned in the lines of 'A', 'B' and 'C' shown in FIG. 3, each of which is parallel to the X-axis direction.", [0046]; while Matsuda utilizes region division and template matching algorithms, it lacks explicit teaching of utilizing frequency analysis across specific directional axes to specify ranges of periodic recesses. Jun fills this gap by teaching the use of Fast Fourier Transformation (FFT) to perform frequency analysis on image pixels in specific intersecting directions (e.g., X-axis and Y-axis) to analyze and detect periodic recesses)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention was made to incorporate Jun into the region detection method of Matsuda in order to more accurately identify, isolate, and analyze target regions having periodic recesses by leveraging Fast Fourier Transformation to convert spatial domain image data into frequency domain data along specific intersecting axes. The combination of Matsuda and Jun also teaches other enhanced capabilities.
Regarding claim 14, the combination of Matsuda and Jun teaches its/their respective base claim(s).
The combination further teaches the profile detection method according to claim 1, wherein the boundary detecting includes detecting, for the each recess region detected in the region detection step, the boundary of the plurality of films based on a change in luminance of a side wall constituting the recess in the one direction.
(Matsuda; "extract coordinates of a boundary line between the processed structure and the background or a boundary line of an interface between different materials in the image of the measurement object", [0049]; "generates, based on the marker and the cross-sectional SEM image that is an input image, an image labeled by region based on luminance information of the input image.", [0035]; "a step of searching from a vertical direction with respect to the set edge detection reference line and extracting an edge point which is a luminance change point from image information", [0009]; Matsuda teaches the extraction of a boundary line at the interface of different materials based on luminance information, specifically by searching from a vertical direction and extracting an edge point which is a luminance change point)
Regarding claim 15, the combination of Matsuda and Jun teaches its/their respective base claim(s).
The combination further teaches the profile detection method according to claim 1, wherein the contour detecting includes detecting, for the each recess region in the image, the contour of the recess based on a change in luminance in the intersecting direction.
(Matsuda; "A luminance distribution signal in an x direction corresponding to the coordinate values of the two points is obtained", [0008]; "extracting an edge point which is a luminance change point from image information", [0009]; Matsuda teaches obtaining a luminance distribution signal in an x direction (the intersecting direction) and extracting an edge point representing a luminance change point)
Regarding claim 16, the combination of Matsuda and Jun teaches its/their respective base claim(s).
The combination further teaches the profile detection method according to claim 1, further comprising:
measuring a dimension of the recess based on a detection result of the contour detecting.
(Matsuda; Fig. 16; “dimension measurement places are set to four places including (1) L1: width of an interface between mask and substrate 606, (2) L2: width of the narrowest part of the substrate 607, (3) L3: height of the mask 608, (4) L4: depth of the trench 609”, [0093])
Regarding claim 17, the combination of Matsuda and Jun teaches its/their respective base claim(s).
The combination further teaches the profile detection method according to claim 1, wherein the data of the image is data of an image of a cross section of a substrate acquired by a scanning electron microscope.
(Matsuda; Fig. 9; test image 900 in Fig. 9 is an “cross-sectional SEM image”, [0108])
Allowable Subject Matter
Claim(s) 4-10 is/are objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening Claim(s).
The following is a statement of reasons for the indication of allowable subject matter:
Claim(s) 4 recite(s) limitation(s) related to calculating pixel luminance averages along one direction and using average profile to detect recess regions. There are no explicit teachings to the above limitation(s) found in the prior art cited in this office action and from the prior art search.
Claim(s) 5-10 depend on claim 4.
Response to Arguments
Applicant's arguments filed on 2/4/2026 with respect to one or more of the pending claims have been fully considered but are moot in view of the new ground(s) of rejection.
Conclusion
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/JIANXUN YANG/
Primary Examiner, Art Unit 2662 4/18/2026
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