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 § 112 The following is a quotation of 35 U.S.C. 112(b): (b ) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention. The following is a quotation of 35 U.S.C. 112 (pre-AIA), second paragraph: The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the appl icant regards as his invention. Claims 1 - 11 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention. Regarding claim 1 , the preamble lines 3-4 recite “when there is a human being identified in an initial image by artificial intelligence ”. It is unclear whether this is a required step or a condition under which the method applies. Claim 1 is directed towards a method, however the recited language is not a clearly defined series of steps. A method claim should be set forth as a series of delineated active steps. Lines 7-10, for example, recite “ calculating a human body coverage area: identifying coordinates of the human being in the initial image to define a human body coverage ar e a, and defining a center point of the human body coverage area as a first focal coordinate ”. It is unclear whether “calculating, identifying, and defining” are three separate steps, a parent step with two sub-steps, or something else . It is also unclear what specifically is meant by “calculating a human body coverage area”. Line 7 defines this as “identifying coordinates”, leaving it unclear how this calculation is being performed, whether it be a geometric computation, a bounding box, or performing a segmentation mask , or something else . Line 15 “calculating a facial coverage area” recites similar issues. Line 13 recites “the cropping frame corresponds to the human body coverage area”. It is unclear what is meant by “corresponds to”, as it could refer to it overlapping, being centered on, being proportionally sized, or that it simply contains it. Pg. 2, Lines 3-4 recite “when it is judged that the cropping frame is covered within the initial image”. It is unclear how this judgement is performed, or what is performing the judgement. “Covered within” recites similar issues to “corresponds to” above, it is ambiguous whether this refers to the crop being fully contained in the image or partially contained up to a threshold. Regarding claim 9 , the preamble lines 1-3 recite “An electronic device… provided in communication with a database, the database receives an initial image and identifies a human being”. The database appears to perform active steps; however the claim is to an electronic device, leaving it undefined whether the database is part of the device or a separate system or how this language alters what is required by the claim . Regarding claims 9 and 11 , both recite language such as “coverage area”, “corresponds to”, “it is judged”, and “covered within”. These are all similarly indefinite under the same analysis as claim 1. Regarding claims 2-8 and 10 , they are dependent on one of claims 1, 9, or 11, leaving them indefinite by virtue of their dependence. Claim Rejections - 35 USC § 103 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. Claim(s) 1 and 4-11 as best understood are rejected under 35 U.S.C. 103 as being unpatentable over Ptucha (US Patent Pub. No. 2013/0108169 A1), published 2013. center 2996565 Regarding claim 1 , Ptucha teaches a n image cropping and processing method for adjusting an aspect ratio, executed by an electronic device reading an executable code, when there is a human being identified in an initial image by artificial intelligence, cropping to the initial image from a first aspect ratio is executed to crop a cropped final image that meets a second aspect ratio (Para. 48, “ A need for re-composition commonly occurs when there is an aspect ratio mismatch between an input digital image and a desired recomposited output aspect ratio for the digital image ”) , comprising the following steps: calculating a human body coverage area: identifying coordinates of the human being in the initial image to define a human body coverage area (Fig. 8, reprinted below, showcases a high priority region bounding box as well as face bounding boxes. See Para. 94, “ Although the methods described herein are done so with respect to human faces, it should be obvious that these methods can be expanded to include any particular object of interest. For example, instead of human faces, we can extract regions based upon human body or human torso ” ) , and defining a center point of the human body coverage area as a first focal coordinate (Para. 67, “ This is accomplished by center cropping on the low priority region as long as doing this does not delete any of the medium priority region. If any of the medium priority region would be cropped by this process, this may be avoided by centering the output image on the medium priority region. If this shift does not crop the high priority region, the result is considered satisfactory. If any of the high priority region would be cropped by this process, the output image is centered on the high priority region. ”, high priority regions are analogous to coverage areas, and the center of these regions are used ) ; calculating a cropping ratio: using the first focal coordinate as a center point to define a cropping frame, the cropping frame has the second aspect ratio, and the cropping frame corresponds to the human body coverage area and is enlarged according to a ratio parameter (Para. 67 above, shows the usage of the center point based on priority regions to define a cropping frame ; Para. 67, “ When attempting to achieve the requested aspect ratio, there may not be enough irrelevant area to use as padding on the top or sides of the low priority region to achieve the requested aspect ratio. In this case, the edges of the image can be padded with non-content borders, the low priority region can be cropped, or we can use external image information to extend the original image in the required direction ”, the cropping frame can be enlarged based on a parameter ) ; calculating a facial coverage area: identifying coordinates of a face of the human being in the initial image to define a facial coverage area, and defining a second focal coordinate of a center point of the facial coverage area (Fig. 8, reprinted above, boxes 811 and 812 show individual facial coverage areas, and 815 shows a medium priority region (facial coverage area) which has a defined center point ) ; and alignment and cropping: defining a center point of the cropping frame as a third focal coordinate, moving the center point of the cropping frame from the third focal coordinate to coincide with the second focal coordinate, and when it is judged that the cropping frame is covered within the initial image, an image of the cropping frame is selected as the cropped final image (Para. 67 above, multiple center points are considered for the final crop ; Para. 69, “ This allows the algorithm to avoid sacrificing pixels inside the low priority region and uses an original image boundary as one of the final image boundaries, as it forms the final output aspect ratio image. ”, the crop is selected as final when the original image content is included in the final image ) . Ptucha does not explicitly disclose defining a human body coverage area. However, they do disclose defining multiple different priority regions as well as teaching that it would be obvious to expand the method to include human body regions (Para. 94). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Ptucha to include defining a human body coverage area. Ptucha teaches a system for automatically cropping an image with an input aspect ratio into a desired output aspect ratio. They focus on defining a facial coverage area as well as multiple priority regions to properly position and compose the crop into the specified aspect ratio. One of ordinary skill in the art would have recognize d that applying the disclosed method to additional portions of the human body constitutes a predictable use of the same technique to a broader but analogous target region . It would have been obvious to expand the face-region method of Ptucha to defin e a human body region , as disclosed by Ptucha (Para. 94). Regarding claim 4 , Ptucha teaches all of the elements of claim 1, as stated above, as well as wherein in the step of calculating a cropping ratio, if the cropping frame exceeds a vertical boundary and/or horizontal boundary of the original size, the cropping frame shifts back according to the exceeded vertical boundary and/or horizontal boundary (Para. 69, “ However, if an image boundary at the top, bottom, left, or right side of the input image is included in this centered low priority region, the algorithm allows the crop box to expand at the opposite side without constraint so that only the original image content is included in the final image. This allows the algorithm to avoid sacrificing pixels inside the low priority region and uses an original image boundary as one of the final image boundaries, as it forms the final output aspect ratio image. ”) . Regarding claim 5 , Ptucha teaches all of the elements of claim 1, as stated above, as well as wherein in the step of alignment and cropping, if the center point of the cropping frame is moved from the third focal coordinate to coincide with the second focus coordinate, and the cropping frame exceeds the vertical boundary or horizontal boundary of the original size, the cropping frame shifts back according to the exceeded vertical boundary and/or horizontal boundary, so as to meet the condition that the cropping frame is covered within the initial image (Para. 67, “ This is accomplished by center cropping on the low priority region as long as doing this does not delete any of the medium priority region. If any of the medium priority region would be cropped by this process, this may be avoided by centering the output image on the medium priority region ”, multiple regions are defined and their center points are used to shift the cropping frame ; Para. 69, “ However, if an image boundary at the top, bottom, left, or right side of the input image is included in this centered low priority region, the algorithm allows the crop box to expand at the opposite side without constraint so that only the original image content is included in the final image ”) . Regarding claim 6 , Ptucha teaches all of the elements of claim 1, as stated above, as well as wherein when there are two or more human beings in the initial image, in the step of calculating a human body coverage area, a first upper boundary coordinate and a first lower boundary coordinate of each human being are identified, in which a first maximum vertical ordinate value and a first minimum horizontal ordinate value are taken to define a human body collection upper boundary coordinate, and a first minimum vertical ordinate value and a first maximum horizontal ordinate value are taken to define a human body collection lower boundary coordinate, the human body collection upper boundary coordinate and the human body collection lower boundary coordinate are used to define the human body coverage area (Para. 55, “ The combined face box area is shown as the dotted rectangle 535 in image 530. It is formed in reference to the leftmost, rightmost, topmost, and bottommost borders of the remaining individual face boxes. ”, See analysis of claim 1 above, performing this area detection on human faces is analogous to performing it on human bodies ) . Regarding claim 7 , the recited elements perform variably the same function as that of claim 6. It is rejected under the same analysis. Regarding claim 8 , the recited terminal device performs variably the same function as the method of claim 1. It is rejected under the same analysis. Regarding claim 9 , the recited electronic device performs variably the same function as the method of claim 1. It is rejected under the same analysis. Regarding claim 10 , Ptucha teaches all of the elements of claim 9, as stated above, as well as wherein the electronic device is a physical host and/or a cloud host (Para. 34, “ In a preferred embodiment as illustrated in FIG. 1, electronic computing system 100 comprises a housing 125 and local memory or storage containing data files 109 ”) . Regarding claim 11 , the recited non-transitory computer-readable recording medium (Para. 46, “ As used herein, terms such as computer or "machine readable medium" refer to any non-transitory medium ”) performs variably the same function as the method of claim 1. It is rejected under the same analysis. Claim(s) 2 -3 as best understood are rejected under 35 U.S.C. 103 as being unpatentable over Ptucha (US Patent Pub. No. 2013/0108169 A1), published 2013, in view of Zhang et al. (NPL, “ AUTO CROPPING FOR DIGITAL PHOTOGRAPHS ”), published 2005. Regarding claim 2 , Ptucha teaches all of the elements of claim 1, as stated above, as well as wherein the covering ratio is defined as when the center point of the cropping frame is moved from the third focal coordinate to coincide with the second focus coordinate, a ratio that the human body coverage area is covered by the cropping frame without exceeding is taken (Para. 67, “ If this shift does not crop the high priority region, the result is considered satisfactory. If any of the high priority region would be cropped by this process, the output image is centered on the high priority region. If this high priority region is nonetheless clipped, once again the image can be padded with borders such that none of the high priority region is cropped out of the final image, or portions of the high priority region can be cropped as a last resort. ”, showcases that it was known to ensure that the cropping frame is properly covering the coverage area ) . Ptucha does not explicitly disclose defining a difference ratio between the coverage area and the cropping frame as smallest according to a setting ratio range. However, they do disclose that the algorithm can be set to fit the final cropping border as tightly as possible to any defined region (Para. 72) . Zhang teaches that an area difference between the human body coverage area and the cropping frame is smallest (Pg. 3, Col. 2, “ if the intersection of cropped rectangle and the attended view is larger, the energy will be larger; If the area of cropped rectangle is larger, the energy will be larger. If the center of cropped rectangle, Pc , is close to the center of the attended view, Pv , the energy will be larger. ”, shows that the larger the difference between the cropping frame and the coverage area, the more energy required ) . Zhang does not explicitly disclose defining a difference ratio according to a setting ratio range. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Ptucha to incorporate the teachings of Zhang to include defining a difference ratio according to a setting range. Ptucha teaches that subject coverage of the cropping frame is important to consider when attempting to produce high-quality crops. Zhang teaches the principle that minimizing excess area between the crop frame and the subject coverage area is a known optimization goal in image cropping. One of ordinary skill in the art would have understood that computing a minimum value from subject geometry and selecting the nearest value within a permitted range is a straightforward way to achieve both goals simultaneously. Regarding claim 3 , Ptucha as modified above teaches all of the elements of claim 2, as stated above, as well as wherein the ratio range is set between 40% and 80% of the original size of the initial image ( Ptucha teaches that crop frame size relative to the subject region is an adjustable parameter (Para. 62). Zhang teaches that the relationship between crop frame area and subject coverage area should be optimized ( Pg. 3, Col. 2 ). Given that the crop frame is established as being larger than the subject and smaller than the original image, one of ordinary skill in the art would have recognized the selection of a specific numerical range within those boundaries as a matter of routine optimization. ) . Conclusion Any inquiry concerning this communication or earlier communications from the examiner should be directed to FILLIN "Examiner name" \* MERGEFORMAT DAVID A WAMBST whose telephone number is FILLIN "Phone number" \* MERGEFORMAT (703)756-1750 . 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