Author: claimsbot

1. A computational proactive process for self-tuned memory leak detection, comprising the steps of:
noting multiple memory usage sample points which show memory usage for a computational service, each noted sample point including a sample time and a memory size, the noted sample points having a mean;
tuning at least some of the noted sample points for memory leak detection by computationally proactively doing at least one of the following: (a) double smoothing noted sample points, (b) identifying a derivative of a sequence of a plurality of linear regression slopes;
statistically analyzing at least one result of the tuning step, thereby computationally proactively determining whether noted memory sizes are trending upward; and
terminating the computational service at least in part in response to a determination that memory sizes are trending upward.
2. The self-tuned memory leak detection process of claim 1, wherein the analyzing step comprises proactively computing a linear regression slope that has an absolute value greater than zero and less than 0.2, and the analyzing step determines that noted memory sizes are holding steady rather than trending upward.
3. The self-tuned memory leak detection process of claim 1, wherein noted sample times include t values which occur at a constant time interval and have a median, and wherein the analyzing step comprises proactively computing a linear regression slope at least in part by resetting an origin to the median of the t values and setting a scale to the constant time interval of the t values.
4. The self-tuned memory leak detection process of claim 1, further comprising computationally selecting (as opposed to receiving as a user input) at least one of the following sample characteristics: sample size, sample rate.
5. The self-tuned memory leak detection process of claim 1, wherein the tuning step comprises computationally proactively excluding any noted sample point that is not within one standard deviation of the mean.
6. The self-tuned memory leak detection process of claim 1, wherein the tuning step comprises computationally proactively double smoothing by performing a second order linear regression based on noted sample points.
7. The self-tuned memory leak detection process of claim 1, wherein the tuning step comprises computationally proactively identifying a derivative of a sequence of linear regression slopes.
8. A computer-readable storage medium configured with data and with instructions that when executed by at least one processor causes the processor(s) to perform a computational proactive process for self-tuned allocated resource usage leak detection, the computer-readable storage medium including one or more of the following physical media: volatile memory, non-volatile memory, fixed in place media, removable media, magnetic media, optical media, CD, DVD, memory stick, flash memory, RAM, ROM, hard disk, magnetic disk, optical disk, EEPROM, the process comprising the steps of:
noting multiple resource usage sample points which show usage of an allocated resource, each noted sample point including a sample time and an allocated resource usage size, the noted sample points having a mean;
tuning at least some of the noted sample points for allocated resource usage leak detection by computationally proactively utilizing at least one of the following self-tuning mechanisms: (a) performance of a second order linear regression based indirectly on noted sample points, (b) identification of a derivative of a sequence of a plurality of linear regression slopes;
statistically analyzing at least one result of the tuning step by proactively computing a linear regression slope and then using the slope in determining whether noted resource usage sizes have a trend; and
controlling another computational process in response to said determining whether noted resource usage sizes have a trend.
9. The configured medium of claim 8, wherein the resource usage sample points show usage of at least one of the following allocated resources: volatile memory, persistent memory.
10. The configured medium of claim 8, wherein the resource usage sample points show usage of at least one of the following allocated resources: disk space, machines in a load balancing system, machines in a cloud computing service.
11. The configured medium of claim 8, wherein the resource usage sample points show usage of at least one allocated resource by at least one of the following: a coroutine, a thread, a task, an interrupt handler, an application, an operating system driver, a procedure, an object method.
12. The configured medium of claim 8, wherein the analyzing step comprises comparing the linear regression slope to a slope magnitude threshold at which the regression slope realizes an upward trend.
13. The configured medium of claim 8, wherein the analyzing step comprises comparing the linear regression slope to a slope magnitude threshold, and the regression slope realizes an upward trend only after crossing the slope magnitude threshold at least a slope frequency threshold number of times, the slope frequency threshold being greater than one.
14. The configured medium of claim 8, wherein the analyzing step comprises computationally proactively utilizing at least two of the self-tuning mechanisms.
15. A computer system equipped with self-tuning resource usage leak detection, the system comprising:
a logical processor;
a memory in operable communication with the logical processor;
a plurality of resource usage sample points residing in the memory, each sample point including a sample time and an allocated resource usage size;
a self-tuning resource usage leak detection code residing in the memory, which upon execution by the processor (i) performs statistical trend analysis on at least a portion of the resource usage sample points, and (ii) in response to the statistical trend analysis, indicates when a service using the resource should be recycled; and
wherein the system also comprises at least one of the following: (a) a plurality of linear regression slopes based on at least some of the resource usage sample points, as well as a second order linear regression that is based on the plurality of linear regression slopes, (b) a plurality of linear regression slopes based on at least some of the resource usage sample points, as well as a derivative of the plurality of linear regression slopes.
16. The system of claim 15, wherein the self-tuning resource usage leak detection code comprises a test to ascertain distance between a sample point and at least one of: a sample points mean, a sample points median.
17. The system of claim 15, wherein the system comprises a plurality of linear regression slopes residing in the memory and based on at least some of the resource usage sample points.
18. The system of claim 15, wherein the system further comprises a resource usage sample points regression slope in the memory, and a regression slope magnitude threshold in the self-tuning resource usage leak detection code.
19. The system of claim 15, wherein the system further comprises a sample size selection code residing in the memory which upon execution by the processor computationally selects (as opposed to having a user select) a sample size for the plurality of resource usage sample points.
20. The system of claim 15, wherein the resource usage sample points show usage of dynamically allocated memory.

The claims below are in addition to those above.
All refrences to claim(s) which appear below refer to the numbering after this setence.

1. A fenestration locking system for a swinging sash or door, comprising:
a) a flexible linear push-pull member, which flexible linear push-pull member is substantially and uniformly flexible throughout its entire length and has multiple actuator engagement sites along its length;
b) a keeper
c) a locking pin assembly, which locking pin assembly has a moveable locking pin and a guide, the moveable locking pin having an actuator that engages at least one of the multiple actuator engagement sites on the flexible linear member when held in position thereon by the guide such that said flexible linear member can then cause said locking pin to move with respect to said locking pin assembly so that an extension engages the keeper when said flexible linear member is moved in a first direction and so that said extension disengages the keeper when said flexible linear member is moved in a second direction; and
d) an actuating assembly, which actuating assembly is used to move said flexible linear member in said first direction and in said second direction, wherein said actuating assembly is comprised of a substantially rigid lever arm with an actuating handle for movement of the lever arm at one end and a drive member at an other end opposite therefrom, the handle not being pivotally connected to said housing other than by said lever arm, the lever arm pivoting about said drive member when the handle is moved, which drive member is slideable in a drive member slot parallel to said flexible linear member and which drive member engages said flexible linear member at one of said multiple actuator engagement sites.
2. A fenestration locking system for a swinging sash or door as described in claim 1, wherein said locking pin assembly is mounted on a fenestration frame and said keeper is oppositely mounted on a window or door mounted in said fenestration frame.
3. A fenestration locking system for a swinging sash or door as described in claim 2, wherein said flexible linear member and actuating assembly are mounted on the fenestration frame.
4. A fenestration locking system for a swinging sash or door as described in claim 1, wherein said keeper is incorporated into a fenestration frame and said locking pin assembly is opposingly mounted on a window or door mounted in said fenestration frame.
5. A fenestration locking system for a swinging sash or door as described in claim 4, wherein said flexible linear member and actuating assembly are incorporated into the window or door mounted in said fenestration frame.
6. A fenestration locking system for a swinging sash or door as described in claim 1, wherein said guide holds said locking pin and said flexible linear member in operative positions.
7. A fenestration locking system for a swinging sash or door as described in claim 6, wherein said guide is inset into a swinging door or sash over said locking pin and said flexible linear member.
8. A fenestration locking system for a swinging sash or door as described in claim 1, wherein said engagement sites are perforations in said flexible linear member.
9. A fenestration locking system for a swinging sash or door as described in claim 8, wherein said actuator has an engagement member that inserts into one of said perforations.
10. A fenestration locking system for a swinging sash or door as described in claim 1, further including a corner member for mounting at a corner of a window or door frame, which corner member guides said flexible linear member around said corner from said actuating assembly to said locking pin assembly.
11. A fenestration locking system for a swinging sash or door as described in claim 1, further including a corner assembly for a corner of a window or door, which corner assembly guides said flexible linear member around said window or door corner from said actuating assembly to said locking pin assembly.
12. A fenestration locking system for a swinging sash or door as described in claim 1, wherein said locking pin moves in a slide slot in said locking pin assembly when moved by said flexible linear member.
13. A fenestration locking system for a swinging sash or door as described in claim 1, wherein said locking pin has a collar by which it is maintained in said locking pin assembly.
14. A fenestration locking system for a swinging sash or door as described in claim 9, wherein said locking pin has an enlarged engagement member by which it is maintained in said locking pin assembly.
15. A fenestration locking system for a swinging sash or door as described in claim 1, wherein said lever arm also has a pivot member, which pivot member is slideable in a pivot member slot transverse to said flexible linear member.
16. A fenestration locking system for a swinging sash or door as described in claim 15, wherein said pivot member is aligned with said drive member slot when the locking system is locked.
17. A fenestration locking system for a swinging sash or door as described in claim 16, wherein said pivot member slot and said drive member slot overlap.
18. A fenestration locking system for a swinging sash or door as described in claim 1, wherein said lever arm has a detachable handle.
19. A fenestration locking system for a swinging sash or door as described in claim 1, wherein said locking pin is hook shaped and said keeper is shaped to engage said hook-shaped locking pin.
20. A fenestration locking system for a swinging sash or door, comprising:
a) a linear member with multiple engagement sites along its length; and
b) an actuating assembly having a housing with a substantially rigid lever arm moveable with respect to said housing, which lever arm has an actuating handle for movement of the lever arm at one end and a drive member at an other end opposite therefrom, the handle not being pivotally connected to said housing other than by said lever arm, the lever arm pivoting about said drive member when the handle is moved, which drive member is slideable in a drive member slot in said housing parallel to said linear member and which drive member can engage said linear member at one of said multiple engagement sites such that said lever arm can then cause said linear member to move with respect to said actuating assembly, and wherein said lever arm also has a transverse pivot member, which pivot member is substantially parallel to said drive member and is slideable in a pivot member slot in said housing transverse to said linear member.
21. A fenestration locking system for a swinging sash or door as described in claim 20, wherein said engagement sites are perforations in said linear member.
22. A fenestration locking system for a swinging sash or door as described in claim 21, wherein said drive member inserts into one of said perforations.
23. A fenestration locking system for a swinging sash or door as described in claim 20, wherein said linear member is flexible.
24. A fenestration locking system for a swinging sash or door as described in claim 20, wherein said linear member is rigid.
25. A fenestration locking system for a swinging sash or door as described in claim 20, further comprising a keeper locking pin attached to said linear member.
26. A fenestration locking system for a swinging sash or door as described in claim 20, wherein said pivot member is aligned with said drive member slot when the locking system is locked.
27. A fenestration locking system for a swinging sash or door as described in claim 26, wherein said pivot member slot and said drive member slot overlap.
28. A fenestration locking system for a swinging sash or door as described in claim 20, wherein said lever arm has a detachable handle.
29. A fenestration locking system for a swinging sash or door as described in claim 25, wherein said keeper locking pin is hook shaped.
30. A fenestration locking system for a swinging sash or door, comprising:
a) a keeper; and
b) an actuating assembly having a housing with a substantially rigid lever arm moveable with respect to said housing, which lever arm has an actuating handle for movement of the lever arm at one end and a drive member at an other end opposite therefrom, the handle not being pivotally connected to said housing other than by said lever arm, the lever arm pivoting about said drive member when the handle is moved, which drive member is slideable in a drive member slot in said housing and can engage said keeper, and wherein said lever arm also has a transverse pivot member, which pivot member is substantially parallel to said drive member and is slideable in a pivot member slot in said housing transverse to said drive member slot.
31. fenestration locking system for a swinging sash or door as described in claim 30, wherein said pivot member is aligned with said drive member slot when the locking system is locked.
32. A fenestration locking system for a swinging sash or door as described in claim 31, wherein said pivot member slot and said drive member slot overlap.
33. A fenestration locking system for a swinging sash or door as described in claim 30, wherein said lever arm has a detachable handle.
34. A fenestration locking system for a swinging sash or door, comprising:
a) a linear member with multiple engagement sites along its length; and
b) an actuating assembly having a housing with a lever arm moveable with respect to said housing, which lever arm is pivotable about a drive member, which drive member is slideable in a drive member slot in said housing parallel to said linear member and which drive member can engage said linear member at one of said multiple engagement sites such that said lever arm can then cause said linear member to move with respect to said actuating assembly, and wherein said lever arm also has a transverse pivot member, which pivot member is substantially parallel to said drive member and is slideable in a linear path in a pivot member slot in said housing transverse to said linear member.
35. A fenestration locking system for a swinging sash or door, comprising:
a) a keeper; and
b) an actuating assembly having a housing with a lever arm moveable with respect to said housing, which lever arm has an actuating handle for movement of the lever arm at one end and a drive member at an other end opposite therefrom, the handle not being pivotally connected to said housing other than by said lever arm, the lever arm being pivotable about said drive member, which drive member is slideable in a drive member slot in said housing and can engage said keeper, and wherein said lever arm also has a transverse pivot member, which pivot member is substantially parallel to said drive member and is slideable in a linear path in a pivot member slot in said housing transverse to said drive member slot.

1. A method for correcting image data for a captured image for lens shading artifacts, the method comprising:
determining a plurality of one dimensional correction curves that can be applied to the image data to correct for lens shading artifacts therein; and
correcting the image data for lens shading artifacts based on the one dimensional curves.
2. The method of claim 1, wherein determining the plurality of one dimensional correction curves comprises determining a first set of correction curves comprising correction curves for each y coordinate in the image data; and determining a second set of correction curves comprising correction curves for each x coordinate in the image data.
3. The method of claim 2, wherein determining the first set of correction curves comprises determining an exact correction curve Lyi(x) for a y coordinate y=y0; and for each y coordinate yi\u2260y0 determining an approximated correction curve Lyi(x) based on the exact correction curve.
4. The method of claim 3, wherein determining an approximated correction curve Lyi(x) based on the exact correction curve comprises selecting at least two segments in the exact correction curve; and determining scaling parameters to morph each segment into a corresponding segment in the approximated curve.
5. The method of claim 4, further comprising storing scaling parameters for a top and a bottom row in the image data and determining the scaling parameters for the intermediate rows by interpolation.
6. The method of claim 2, wherein determining the second set of correction curves comprises determining an exact correction curve LXi(y) for an x coordinate x=x0; and for each x coordinate xi\u2260x0 determining an approximated correction curve Lxi(y) based on the exact correction curve.
7. The method of claim 6, wherein determining an approximated correction curve Lxi(y) based on the exact correction curve comprises selecting at least two segments in the exact correction curve; and determining scaling parameters to morph each segment into a corresponding segment in the approximated curve.
8. The method of claim 7, further comprising storing scaling parameters for a leftmost and a rightmost column in the image data and determining the scaling parameters for the intermediate columns by interpolation.
9. The method of claim 3, wherein the coordinate y=y0 runs through a brightest spot in the image data.
10. The method of claim 6, wherein the coordinate x=x0 runs through a brightest spot in the image data.
11. An image processor, comprising:
an image buffer to store image data for a captured image; and
lens shading correction logic to perform a method for correcting image data for lens shading artifacts, the method comprising:
determining a plurality of one dimensional correction curves that can be applied to the image data to correct for lens shading artifacts therein; and
correcting the image data for lens shading artifacts based on the one dimensional curves.
12. The image processor of claim 11, wherein the plurality of one dimensional correction curves is determined by determining a first set of correction curves comprising correction curves for each y coordinate in the image data; and determining a second set of correction curves comprising correction curves for each x coordinate in the image data.
13. The image processor of claim 12, wherein determining the first set of correction curves comprises determining an exact correction curve Lyi(x) for a y coordinate y=y0; and for each y coordinate yi\u2260y0 determining an approximated correction curve Lyi(x) based on the exact correction curve.
14. The image processor of claim 13, wherein determining an approximated correction curve Lyi(x) based on the exact correction curve comprises selecting at least two segments in the exact correction curve; and determining scaling parameters to morph each segment into a corresponding segment in the approximated curve.
15. The image processor of claim 14, the method for correcting the image data further comprises storing scaling parameters for a top and a bottom row in the image data and determining the scaling parameters for the intermediate rows by interpolation.
16. A camera system, comprising:
camera optics;
an image sensor positioned so that light passing through the camera optics impinges on the image sensor; and
an image processor coupled to the image sensor to receive image data for a captured image therefrom, wherein the image processor comprises lens shading correction logic to perform a method for correcting the image data for lens shading artifacts, the method comprising:
determining a plurality of one dimensional correction curves that can be applied to the image data to correct for lens shading artifacts therein; and
correcting the image data for lens shading artifacts based on the one dimensional curves.
17. The camera system of claim 16, wherein determining the plurality of one dimensional correction curves comprises determining a first set of correction curves comprising correction curves for each y coordinate in the image data; and determining a second set of correction curves comprising correction curves for each x coordinate in the image data.
18. The camera system of claim 17, wherein determining the first set of correction curves comprises determining an exact correction curve Lyi(x) for a y coordinate y=y0; and for each y coordinate yi\u2260y0 determining an approximated correction curve Lyi(x) based on the exact correction curve.
19. The camera system of claim 18, wherein determining an approximated correction curve Lyi(x) based on the exact correction curve comprises selecting at least two segments in the exact correction curve; and determining scaling parameters to morph each segment into a corresponding segment in the approximated curve.
20. The camera system of claim 19, wherein the method for correcting the image data further comprises storing scaling parameters for a top and a bottom row in the image data and determining the scaling parameters for the intermediate rows by interpolation.

The claims below are in addition to those above.
All refrences to claim(s) which appear below refer to the numbering after this setence.

1. A method implemented by a computer system, the method for detecting digital image compositing, said method comprising the steps of:
finding an uncompressed digital image as a portion of a larger digital image having a higher likelihood of exhibiting forgery as compared to other portions of the larger digital image, the portion being found using a region-of-interest detector;
detecting a first artifact in the uncompressed digital image, said first artifact being characteristic of an earlier compression of said uncompressed digital image with a predetermined compression algorithm;
evaluating an interpolation marker in said uncompressed digital image to provide interpolation results;
during said evaluating, counteracting a second artifact of said compression algorithm;
classifying said larger digital image responsive to said interpolation results; and
storing results of the classifying in a computer-readable memory device.
2. The method of claim 1 wherein said second artifact and said interpolation marker are different periodicities in said image.
3. The method of claim 2 wherein said first artifact is a blocking artifact.
4. The method of claim 1 wherein said first artifact is a blocking artifact.
5. The method of claim 1 wherein said method further comprises decompressing said portion of the larger digital image to generate the uncompressed digital image.
6. The method of claim 1 wherein said region of interest detector is selected from the group consisting of: face detectors, main subject detectors, skin region detectors, sky detectors, other object detectors, and combinations of two of more of said detectors of said group.
7. The method of claim 1 further comprising repeating said finding, detecting, evaluating, and counteracting steps with an additional digital image.
8. The method of claim 7 wherein said uncompressed digital image and said additional digital image are each different parts of the larger digital image; and wherein said classifying further comprises classifying said larger digital image responsive to said interpolation results.
9. The method of claim 8 further comprising accepting user input designating at least said uncompressed digital image or said additional digital image.
10. The method of claim 7 wherein said uncompressed digital image and said additional digital image are each a frame, or a portion of a frame, of a video sequence.
11. The method of claim 1 wherein said evaluating further comprises:
generating a one-dimensional periodicity signal from the uncompressed digital image;
computing a Discrete Fourier Transform of said periodicity signal; and
detecting a first set of peaks in the said Discrete Fourier transform; and

wherein said counteracting further comprises excluding from said detecting a second set of peaks in said Discrete Fourier Transform.
12. A computer program product for detecting digital image compositing, the computer program product comprising computer readable storage medium having a computer program stored thereon for performing the steps of claim 1.
13. A system for detecting digital image compositing, said method comprising the steps of:
means for finding an uncompressed digital image as a portion of a larger digital image having a higher likelihood of exhibiting forgery as compared to other portions of the larger digital image;
means for detecting a first artifact in said uncompressed digital image, said first artifact being characteristic of an earlier compression of said uncompressed digital image with a predetermined compression algorithm;
means for evaluating an interpolation marker in said uncompressed digital image to provide interpolation results;
means for counteracting a second artifact of said compression algorithm during said evaluating; and
means for classifying said larger digital image responsive to said interpolation results.
14. A method implemented by a computer system, the method for detecting digital image compositing, said method comprising the steps of:
detecting the presence of a first artifact in said an uncompressed digital image, said first artifact being characteristic of an earlier compression of said digital image with a predetermined compression algorithm;
finding a plurality of different regions of said uncompressed digital image, at least one of the plurality of different regions having a higher likelihood of exhibiting forgery as compared to another of the plurality of different regions of the uncompressed digital image, at least some of the plurality of different regions being found using a region-of-interest detector;
evaluating an interpolation marker in the different regions to provide interpolation results of each of said regions;
when said first artifact is present in said digital image, counteracting a second artifact of said compression algorithm during said evaluating;
classifying said image responsive to said interpolation results; and
storing results of the classifying in a computer-readable memory device.
15. The method of claim 14 wherein said first artifact is a blocking artifact and said second artifact and said interpolation marker are different periodicities in said image.
16. The method of claim 14 wherein said classifying further comprises comparing interpolation results of at least some of said regions.
17. The method of claim 14 wherein said evaluating of each of said regions further comprises:
generating a one-dimensional periodicity signal from the corresponding region;
computing a Discrete Fourier Transform of said periodicity signal; and
detecting a first set of peaks in the said Discrete Fourier transform; and

wherein said counteracting further comprises excluding from said detecting a second set of peaks in said Discrete Fourier Transform.
18. A method implemented by a computer system, the method for detecting digital image compositing, said method comprising the steps of:
finding an uncompressed digital image as a portion of a larger digital image having a higher likelihood of exhibiting forgery as compared to other portions of the larger digital image, the portion being found using a region-of-interest detector;
detecting a blocking artifact in the uncompressed digital image;
identifying a compression-induced periodicity artifact associated with said blocking artifact;
evaluating periodicity in said uncompressed digital image to provide interpolation results;
during said evaluating, counteracting said compression-induced periodicity artifact;
classifying said larger digital image responsive to said interpolation results; and
storing results of the classifying in a computer-readable memory device.
19. The method of claim 8, wherein said classifying further comprises comparing interpolation results of said uncompressed digital image and said additional digital image.
20. The method of claim 19, wherein said additional digital image has a lower likelihood of exhibiting forgery as compared to the uncompressed digital image portion of the larger digital image.
21. The system of claim 13, wherein the finding, detecting, evaluating, and counteracting are performed for an additional portion of the larger digital image, and wherein the classifying further comprises comparing interpolation results of each of the uncompressed digital image and the additional portion of the larger digital image.
22. The method of claim 18 wherein the finding, detecting, evaluating, and counteracting steps are performed for an additional portion of the larger digital image, and wherein the classifying further comprises comparing interpolation results of each of the uncompressed digital image and the additional portion of the larger digital image.