The present invention relates to a method of processing an image.
Face detection and tracking is well known in image processing for example as described in European Patent No. EP2052347 (Ref: FN-143). These techniques enable one or more face regions within a scene being imaged to be readily delineated and to allow for subsequent image processing based on this information. Such image processing can include face recognition which attempts to identify individuals being imaged; auto-focussing by bringing a detected and/or selected face region into focus; or defect detection and/or correction of the face region(s).
It is well known that anthropometric information can be employed in processing face regions. For example, knowledge of an expected face size can be used for in face detection or filtering for example, for example, for falsing analysis of red-eye candidates as described in EP1654865 (Ref: FN-101-CIP).
However, problems can occur if a scene being imaged includes any faces which do not conform to common anthropometric rules. For example, if a scene includes a billboard with a very large human face, processing based on common anthropometric rules could indicate a real subject much closer to the camera than the billboard. This could for example, indicate that the camera should focus at a much shorter distance and if it were to do so, an out of focus image would be produced.
Correspondingly, if a scene includes a small child, then detection of their face could indicate a subject much further from the camera than the child. This could for example, indicate that the camera should focus at a much longer distance and again, if it were to do so, an out of focus image would be produced.
For the purposes of the present disclosure, the term “false face” will be used to indicate regions of an image including detected faces which do not conform to normal anthropometric rules.
In some cases, failure to appreciate that a false face has been detected could cause an isolated image to be acquired with incorrect focus, and in a video camera, capturing a stream of images of a scene, it is possible that the camera might lose its ability of focus properly.
Nonetheless, it will be appreciated that the above outlined problems could equally arise if attempting to base image processing on any falsely detected object. For example, some image processing could be based on rules relating to the dimensions of automobiles and clearly image of false automobiles, for example, displayed on billboards, could be captured which could cause problems.
According to the present invention, there is provided an image processing method according to claim 1.
In a further aspect, there is provided an image processing device arranged to perform the method of claim 1.
In a still further aspect, there is provided a computer program product comprising computer readable instructions, which when executed in an image processing device are arranged to perform the method of claim 1.
Embodiments of the present invention provide rapid auto-focus based on detected faces but without being adversely affected by false faces and indeed being able to focus properly on such false faces.
Alternative embodiments provide auto-focusing based on any detectable object of interest with a feature with known dimensions.
An embodiment of the invention will now be described, by way of example, with reference to the accompanying drawings, in which:
Referring now to
When a face is in a hyper-focal range of a lens, with given distance to the subject (ds), in order to get a focused image, the lens should be displaced by a distance (ld), so that the distance between the lens and an image sensor is f+ld.
Thus, distance to subject versus lens displacement are linked by the formula: 1/f=1/ds+1/(f+ld) as illustrated graphically in
When a required lens displacement ld is determined, a camera can select a required digital-to-analog convert (DAC) code for displacing a lens assembly incorporating the lens as required to properly maintain focus on the face.
An image processing system using detected faces to assist with focusing can operate as follows:
Consider for example, if a false face with an eye distance ed=2 cm (a small face) had in fact been detected at step 1 above. A focusing algorithm, using an ed=7 cm would consider the small face to be very far, determining a very large distance to the subject (ds) and a corresponding DAC Code, probably close to infinity. This would result in a highly defocused image.
Referring now to
This overwriting of the standard eye distance should be kept only as long as the false face is tracked. Once the face is lost, step 210, the common eye distance (ed=7 cm) is used again for newly detected faces.
Otherwise, for each new image to be acquired, the required DAC code is calculated based on the calculated eye distance, step 209.
It will be appreciated that a full sweep is not necessarily required to each time a new face is detected and that for example, a modified sweep can be performed to determine if a detected face is false, step 212. So, for example, for the lens displacement at which an image including a newly detected face is acquired, the lens can be displaced to a lens displacement position either side of the image acquisition lens displacement.
If the sharpness of the face region at the image acquisition lens displacement is a maximum relative to the sharpness for the adjacent lens displacement positions, then the estimation is regarded as good. In this case, image processing continues at step 209 to determine the required DAC code for each new image in which the face region continues to be detected based on the assumed eye distance ed=7 cm.
However, if the sharpness of the face region is not a maximum, it indicates that the face within the newly detected face region is false, so triggering a full sweep, step 204, to determine ed_sweep as described above.
It will be appreciated that steps 204 to 208 need only be performed once for a detected object; however, the steps could also be repeated in response to a sharpness for the face region dropping below a given threshold.
The present invention can be employed wherever image processing relies on detecting an object having a feature with known dimensions, so enabling a temporary rather than assumed set of dimensions to be used for the object while it is being tracked and enabling focus to be maintained on the object while it is being tracked.
It will be seen that the present invention can be employed for image processing other than auto-focusing and for example, can be employed to temporarily overwrite an assumed object dimension for the purposes of processing images containing a false version of such an object.
This application claims the benefit and priority to U.S. Provisional Application Ser. No. 62/089,369, filed Dec. 9, 2014. The contents of all of these documents are incorporated herein by reference, as if fully set forth herein. The applicants hereby rescind any disclaimer of claim scope in the parent application or the prosecution history thereof and advise the USPTO that the claims in this application may be broader than any claim in the parent applications.
Number | Name | Date | Kind |
---|---|---|---|
20080199056 | Tokuse | Aug 2008 | A1 |
20090190023 | Mise | Jul 2009 | A1 |
20090256953 | Yasuda | Oct 2009 | A1 |
20090310029 | Tanaka | Dec 2009 | A1 |
20100157135 | Dossaji | Jun 2010 | A1 |
20100208091 | Chang | Aug 2010 | A1 |
20110002680 | Narasimha | Jan 2011 | A1 |
20120044408 | Sasaki | Feb 2012 | A1 |
20120075492 | Nanu | Mar 2012 | A1 |
20120218456 | Sweet, III | Aug 2012 | A1 |
20120320258 | Nakagawara | Dec 2012 | A1 |
20140160019 | Anda | Jun 2014 | A1 |
20150206338 | Miura | Jul 2015 | A1 |
20160140406 | Chu | May 2016 | A1 |
20160150215 | Chen | May 2016 | A1 |
Number | Date | Country |
---|---|---|
WO2005015896 | Feb 2005 | WO |
WO2008018887 | Feb 2008 | WO |
Number | Date | Country | |
---|---|---|---|
20160165129 A1 | Jun 2016 | US |
Number | Date | Country | |
---|---|---|---|
62089369 | Dec 2014 | US |