Patent Description:
It is known to perform a manual diagnostic test or check of a camera flash of a mobile electronic device in which a user or operator of the mobile electronic device needs to provide feedback indicating whether or not the camera flash of the mobile electronic device actually operates when enabled. However, such manual diagnostic tests or checks are time-consuming and are susceptible to human error or fraud.

<CIT> discloses a system for verifying a lamp operation which includes: a camera for acquiring an image around the vehicle; and an image processor for determining whether the lamp is broken based on the image acquired by the camera, in which the image processor receives a turn on state of the lamp through internal communication of the vehicle connected to the lamp and determines whether the lamp is broken by comparing images before and after the lamp is turned on.

<CIT> discloses a non-transitory machine-readable storage medium which includes instructions to determine whether a light source associated with a camera has a defect. When executed, the instructions cause a processor of a computing device to cause the light source associated with the camera to emit light toward a reflective test surface to illuminate the reflective test surface, wherein the light source integrated with the camera is configured to emit light during normal operation of the camera. The instructions further cause the processor to cause the camera to capture an image of the reflective test surface illuminated by the light source. The instructions further cause the processor to analyze the captured image to determine whether the light source has a defect. The instructions further cause the processor to output an indication of the defect when determined.

According to an aspect of the present invention there is provided a method according to claim <NUM> for use in testing an operational status of a light source for illuminating a scene.

Optional features of the method are defined according to dependent claims <NUM> to <NUM>.

According to an aspect of the present invention there is provided an application according to claim <NUM> for a mobile electronic device comprising a camera and a light source, or an application for a server configured for communication with a mobile electronic device, which mobile electronic device comprises a camera and a light source.

According to an aspect of the present disclosure there is provided a method for use in testing an operational status of a light source for illuminating a scene, the light source having a fixed spatial relationship relative to a camera, and the method comprising:.

Such a method may be used for testing the operational status of a light source and, in particular, though not exclusively, for use in automatically testing the operational status of a camera flash of a mobile electronic device.

The one or more camera settings may comprise an ISO setting of an image sensor of the camera, an exposure index of an image sensor of the camera, a sensitivity setting of an image sensor of the camera, or a gain setting of an image sensor of the camera.

The one or more camera settings may comprise a shutter speed or an exposure time of the camera.

The one or more camera settings may comprise an aperture setting, an f-stop, or an f-number of the camera.

The one or more image properties may comprise an image brightness parameter.

The image brightness parameter may comprise an average brightness of an image or an average intensity of an image, or an average brightness or an average intensity of a pre-defined portion or a pre-defined area of an image.

The one or more image properties may comprise an image file size.

The method may comprise reading the first and second images from the camera.

The method may comprise determining, for each of the first and second images, the light source settings, the one or more camera settings, and the one or more image properties.

The method may comprise extracting from metadata associated or stored with each of the first and second images, the light source settings, the one or more camera settings, and the one or more image properties for each of the first and second images.

The method may comprise reading the light source settings, the one or more camera settings, and the one or more image properties for the first and second images from the camera.

The method may comprise determining the image properties of the first and second images from image data of the first and second images.

The method may comprise determining whether the first and second images are images of the same scene.

The method may comprise selecting each predetermined camera setting criterion and each predetermined image property criterion based at least in part on the corresponding camera setting value and/or the corresponding image property value when the camera captures the first image. This may be advantageous where the first image captures a scene which is relatively bright.

The method may comprise determining a positive test result indicating that the light source is operational, or that the light source operates correctly or in compliance with a predetermined performance specification if:.

The method may comprise determining a negative test result indicating that the light source is non-operational, or that the light source is faulty or fails to comply with a predetermined performance specification if:
the first and second images are determined to be images of the same scene; and at least one of:.

The method may comprise determining a negative test result indicating that the light source is non-operational, or that the light source is faulty or fails to comply with a predetermined performance specification if:.

The method may comprise using an image processing algorithm such as a machine learning algorithm to identify any localised feature or artefact of a greater brightness than one or more adjacent areas or regions of the first and/or second images.

The method may comprise determining an inconclusive test result for the operational status of the light source if it is determined that the first and second images are not images of the same scene.

Determining whether the first and second images are images of the same scene may comprise:.

Determining whether the first and second images are images of the same scene may comprise using an image processing algorithm to identify the object in the first image and to identify the same object in the second image. The image processing algorithm may be based on a machine learning algorithm.

The one or more properties of the object may comprise one or more of: a size of the object, an aspect ratio of the object, a position of the object and an orientation of the object.

Determining whether the first and second images are images of the same scene may comprise determining that the first and second images are images of the same scene if a difference between the quantitative degree of similarity between the first and second images is less than a predetermined threshold value.

The quantitative degree of similarity between the first and second images may comprise a cross-correlation between the first and second images or a cross-correlation between corresponding portions of the first and second images.

Determining whether the first and second images are images of the same scene may comprise determining that the first and second images are images of the same scene if a difference between the determined distance from the camera to the object at the predetermined position in the first image and the determined distance from the camera to the object at the predetermined position in the second image is less than a predetermined threshold value.

Measuring the distance from the camera to the object at the time of capture of each of the first and second images may comprise executing an augmented reality (AR) application on a computing device. Such an application may comprise a third-party AR library, such as ARCore, which provides an application programming interface (API) to the AR application. The computing device may be configured for communication with the camera. Further, the camera may form part of, be defined by, or be fixed or attached to, the computing device.

Measuring the distance from the camera to the object at the time of capture of each of the first and second images may comprise:.

The emitter and the detector may have a fixed spatial relationship with respect to the camera. The emitter and the detector may be fixed or attached to the camera.

The modulated electromagnetic radiation may comprise amplitude modulated electromagnetic radiation.

The modulated electromagnetic radiation may comprise a stream of pulses of electromagnetic radiation.

The modulated electromagnetic radiation may comprise frequency modulated electromagnetic radiation.

The electromagnetic radiation may comprise light, for example visible or infrared (IR) light.

The emitter may comprise a light emitter.

The light emitter may comprise a light emitting diode (LED). The light emitter may comprise a source of coherent light such as a laser, for example a laser diode.

The emitter may comprise one or more LEDs.

The emitter may comprise one or more laser diodes.

The detector may comprise an optical detector such as a photodiode.

The detector may comprise a time of flight (ToF) camera.

Determining whether the first and second images are images of the same scene may comprise determining that the first and second images are images of the same scene if the size of any movements of the camera are less than one or more predetermined threshold values.

Determining whether the first and second images are images of the same scene may comprise determining that the first and second images are images of the same scene if a difference between the determined locations of the camera at the times of capture of the first and second images are less than a corresponding predetermined location threshold value and a difference between the determined orientations of the camera at the times of capture of the first and second images are less than a corresponding predetermined orientation threshold value.

The light source may comprise a camera flash provided with, housed with, or fixed or attached to, the camera.

The camera and the light source may form part of, be defined by, or be fixed or attached to, a device such as a computing device.

The computing device may be a mobile electronic device comprising a mobile phone, a smart phone, a cell phone, or a tablet, for example. The computing device may be a desktop computer, a laptop computer, or a workstation. The computing device may be an Internet-of-Things (IoT) device such as a smart home appliance or a smart security device.

The camera and the light source may form part of, be defined by, or be fixed or attached to, a security system for a building, a fixed structure, or an enclosed area or space.

The camera and the light source may form part of, be defined by, or be fixed or attached to, a vehicle.

The light source may comprise, or be defined by, a light source provided with the vehicle such as a head light or a tail light of the vehicle.

According to an aspect of the present disclosure there is provided an application for a mobile electronic device comprising a camera and a light source, or for a server configured for communication with a mobile electronic device comprising a camera and a light source, wherein, when executed by a processor of the mobile electronic device or a processor of the server, the application causes the mobile electronic device to perform any of the methods described above.

According to an aspect of the present disclosure there is provided a mobile electronic device comprising the application as described above.

According to an aspect of the present disclosure there is provided a server comprising the application as described above.

It should be understood that any one or more of the features of any one of the foregoing aspects of the present disclosure may be combined with any one or more of the features of any of the other foregoing aspects of the present disclosure.

Various apparatus and methods for use in testing the operational status of a light source will now be described by way of non-limiting example only with reference to the following drawings of which:.

Referring initially to <FIG> there is shown a system, generally designated <NUM>, for use in automatically testing the operational status of a camera flash of the mobile electronic device <NUM>. The mobile electronic device <NUM> includes a memory <NUM>, a processor <NUM>, a communication interface <NUM>, a user interface in the form of a touchscreen <NUM>, a camera <NUM>, a light source in the form of a camera flash <NUM>, an infrared (IR) source in the form of an infrared light emitting diode (LED) <NUM>, a photodiode <NUM> which is configured for detection of infrared light emitted by the LED <NUM> and reflected back onto the photodiode <NUM>, a motion sensor in the form of an accelerometer <NUM> and an antenna <NUM>. The memory <NUM> stores a diagnostics application <NUM>.

The system <NUM> includes a server which is generally designated <NUM> and which is located remotely from the mobile electronic device <NUM>. The server <NUM> includes a memory <NUM>, a processor <NUM>, a communication interface <NUM>, and a user interface <NUM>. The memory <NUM> stores a computer program in the form of a diagnostics application <NUM>, data <NUM> relating to one or more images captured by the mobile electronic device <NUM>, and diagnostic information <NUM> relating to the operational status of the camera flash <NUM> of the mobile electronic device <NUM>.

As shown in <FIG>, the mobile electronic device <NUM> and the server <NUM> are configured for communication over the cloud <NUM> via the communication interface <NUM> and antenna <NUM> of the mobile electronic device <NUM> and the communication interface <NUM> of the server <NUM>.

When executed by the processor <NUM> of the mobile electronic device <NUM>, the diagnostics application <NUM> causes the mobile electronic device <NUM> to perform a method for automatically testing the operational status of the camera flash <NUM> of the mobile electronic device <NUM>.

As illustrated in <FIG>, the method <NUM> begins at step <NUM> with the mobile electronic device <NUM> disabling the camera flash <NUM> and prompting a user of the mobile electronic device <NUM>, via the user interface <NUM>, to use the camera <NUM> to capture a first image <NUM> of a scene. The method continues at step <NUM> with the mobile electronic device <NUM> enabling the camera flash <NUM> and prompting the user, via the user interface <NUM>, to use the camera <NUM> to capture a second image <NUM> of the same scene.

As will be described in more detail below, the processor <NUM> of the mobile electronic device <NUM> then determines a test result indicating the operational status of the camera flash <NUM> based at least in part on a light source setting indicating that the camera flash <NUM> is disabled when the camera <NUM> captures the first image, a light source setting indicating that the light source is enabled when the camera captures the second image, one or more camera settings when the camera <NUM> captures the first and second images, and one or more image properties of the first and second images.

Specifically, at step <NUM>, the processor <NUM> of the mobile electronic device <NUM> extracts from metadata provided with the image data of the first and second images: the light source settings associated with the first and second images; the camera settings when the camera <NUM> captures the first and second images; and the one or more image properties of the first and second images. Specifically, the processor <NUM> of the mobile electronic device <NUM> extracts or accesses the metadata provided with the image data of the first and second images programmatically via an application programming interface (API) for the camera <NUM>.

As illustrated in <FIG>, the camera settings include an ISO setting and a shutter speed or an exposure time used by the camera when the camera <NUM> captures the first and second images <NUM>, <NUM>, and the image properties include image brightness parameter values associated with the first and second images <NUM>, <NUM> and image file sizes of the first and second images <NUM>, <NUM>. The one or more brightness parameter values of each of the first and second images <NUM>, <NUM> may, for example, comprise an average brightness or an average intensity of each of the first and second images <NUM>, <NUM> or an average brightness or an average intensity of a pre-defined portion or a pre-defined area of each of the first and second images <NUM>, <NUM>.

The method continues at step <NUM> of <FIG> with the processor <NUM> of the mobile electronic device <NUM> then determining whether the first and second images are images of the same scene. Specifically, the processor <NUM> of the mobile electronic device <NUM> compares the first and second images <NUM>, <NUM> and determines whether the first and second images correspond to images of the same scene based on the results of the comparison of the first and second images. More specifically and, with reference to <FIG>, the processor <NUM> of the mobile electronic device <NUM> determines a distance from the camera <NUM> to an object <NUM> located at a predetermined position in the first image <NUM> and the processor <NUM> determines a distance from the camera <NUM> to the object <NUM> located at a predetermined position in the second image <NUM>, which predetermined position in the second image <NUM> corresponds to the predetermined position in the first image <NUM>. The processor <NUM> then determines that the first and second images <NUM>, <NUM> are images of the same scene if the determined distance from the camera <NUM> to the object <NUM> at the predetermined position in the first image <NUM> and the determined distance from the camera <NUM> to the object <NUM> at the predetermined position in the second image <NUM> comply with a predetermined distance criterion. For example, the processor <NUM> determines that the first and second images <NUM>, <NUM> are images of the same scene if a difference between the determined distance from the camera <NUM> to the object <NUM> at the predetermined position in the first image <NUM> and the determined distance from the camera <NUM> to the object <NUM> at the predetermined position in the second image <NUM> is less than a predetermined threshold value. The processor <NUM> causes the camera <NUM> to measure the distance from the camera <NUM> to the object <NUM> at the time of capture of the first image <NUM> and to measure the distance from the camera <NUM> to the object <NUM> at the time of capture of the second image <NUM>. More specifically, the processor <NUM> causes the LED <NUM> to transmit modulated infrared light to the object <NUM> and the processor <NUM> causes the photodiode <NUM> to detect a portion of the transmitted modulated infrared light that is reflected from the object <NUM>. The processor <NUM> then determines the distance from the camera <NUM> from the delay between transmitting the modulated infrared light from the LED <NUM> and detecting the reflected modulated infrared light at the photodiode <NUM>. One of ordinary skill in the art will understand that a variety of distance measurement techniques are possible using modulated infrared light.

For example, the modulated infrared light may be amplitude modulated and the distance from the camera <NUM> to the object <NUM> may be determined from the delay between transmitting an amplitude modulated feature of the amplitude modulated infrared light from the LED <NUM> and the arrival of the same amplitude modulated feature of amplitude modulated infrared light at the photodiode <NUM>. The amplitude modulated infrared light may, for example, comprise a stream of pulses of infrared light and the distance from the camera <NUM> to the object <NUM> may be determined from the delay between transmitting a pulse of infrared light from the LED <NUM> and the arrival of the same pulse of infrared light at the photodiode <NUM>. Alternatively, the modulated infrared light may be frequency modulated and the distance from the camera <NUM> to the object <NUM> may be determined from a delay determined from a difference between a frequency of the frequency modulated infrared light transmitted from the LED <NUM> and a frequency of the frequency modulated infrared light arriving at the photodiode <NUM>. Additionally or alternatively, the processor <NUM> causes an augmented reality (AR) application to measure the distance from the camera <NUM> to the object <NUM> at the time of capture of the first image <NUM> and to measure the distance from the camera <NUM> to the object <NUM> at the time of capture of the second image <NUM>. More specifically, the processor <NUM> executes an AR application causing the camera to first quantify the dimensional space between the camera <NUM> and the object <NUM> and then to measure the distance from the camera <NUM> to the object <NUM>. Such an application may comprise a third-party AR library, such as ARCore, which provides an application programming interface (API) to the AR application.

Referring now to <FIG>, the method continues at step <NUM> with the processor <NUM> determining, for each of the one or more camera settings, whether a camera setting difference between a camera setting value associated with the first image <NUM> and a camera setting value associated with the second image <NUM> complies with a corresponding predetermined camera setting criterion. Similarly, at step <NUM>, the processor <NUM> determines, for each of the one or more image properties, whether an image property difference between an image property value associated with the first image <NUM> and an image property value associated with the second image <NUM> complies with a corresponding predetermined image property criterion.

At step <NUM>, the processor <NUM> determines whether one or more of the camera setting differences comply with the corresponding predetermined criterion and whether one or more of the image property differences comply with the corresponding predetermined criterion.

If the processor <NUM> determines that one or more of the camera setting differences comply with the corresponding predetermined criterion and that one or more of the image property differences comply with the corresponding predetermined criterion, at step <NUM> the processor <NUM> determines a positive test result indicating that the light source is operational, or that the light source operates correctly or in compliance with a predetermined performance specification and returns the positive test result to a user of the mobile electronic device <NUM> via the user interface <NUM> and/or returns the positive test result to the server <NUM> via the communication interfaces <NUM>, <NUM> and the cloud <NUM> for storage as the diagnostic information <NUM> in the memory <NUM> of the server <NUM>.

If the processor <NUM> determines that one or more of the camera setting differences fails to comply with the corresponding predetermined criterion or that one or more of the image property differences fails to comply with the corresponding predetermined criterion, at step <NUM> the processor <NUM> determines a negative test result indicating that the light source is non-operational, or that the light source is faulty or fails to comply with a predetermined performance specification and returns the negative test result to a user of the mobile electronic device <NUM> via the user interface <NUM> and/or returns the negative test result to the server <NUM> via the communication interfaces <NUM>, <NUM> and the cloud <NUM> for storage as the diagnostic information <NUM> in the memory <NUM> of the server <NUM>.

If at step 106c, the processor <NUM> determines the determined distances from the camera <NUM> to the object <NUM> at the predetermined position in the first and second images <NUM>, <NUM> do not comply with the corresponding predetermined criterion, the processor <NUM> determines that the first and second images <NUM>, <NUM> are images of different scenes at step 106e. At step <NUM>, the processor <NUM> then determines that the test result is inconclusive and returns the inconclusive test result to a user of the mobile electronic device <NUM> via the user interface <NUM> and/or returns the inconclusive test result to the server <NUM> via the communication interfaces <NUM>, <NUM> and the cloud <NUM> for storage as the diagnostic information <NUM> in the memory <NUM> of the server <NUM>.

In one specific example of the method for automatically testing the operational status of the camera flash <NUM> of the mobile electronic device <NUM> described with reference to <FIG>, the one or more camera settings extracted from the metadata of the first and second images <NUM>, <NUM> may comprise an ISO setting of the camera <NUM> and a shutter speed setting of the camera <NUM>, the one or more image properties extracted from the metadata of the first and second images <NUM>, <NUM> may comprise a brightness parameter and an image file size, and experiments with several different makes and models of smartphone have demonstrated that the camera flash <NUM> can be considered to be operational if at least two of the following predetermined criteria are satisfied:.

Conversely, the camera flash <NUM> can be considered to be non-operational if one or none of the predetermined criteria (i)-(iv) above are satisfied.

In a variant of the method for automatically testing the operational status of the camera flash <NUM> of the mobile electronic device <NUM> described with reference to <FIG>, the steps <NUM>, <NUM>, <NUM>, <NUM>, <NUM> and <NUM> illustrated in <FIG> may be replaced with the steps <NUM>, <NUM>, <NUM>, <NUM> and <NUM> illustrated in <FIG>. Specifically, at step <NUM>, the processor <NUM> determines whether the second image <NUM> has a localised feature or artefact of a greater brightness than one or more adjacent areas or regions of the second image <NUM>. Such a localised feature or artefact of greater brightness than the one or more adjacent areas or regions of the second image <NUM> may arise as a result of a reflection such as a specular reflection of the camera flash <NUM> from an object in the scene.

If the processor <NUM> determines that the second image <NUM> has a localised feature or artefact of a greater brightness than one or more adjacent areas or regions of the second image <NUM> at step <NUM>, the method continues at step <NUM> with the processor <NUM> determining whether the first image <NUM> has a localised feature or artefact of a greater brightness than one or more adjacent areas or regions of the first image <NUM>, which localised feature or artefact of the first image <NUM> is located at a position in the first image <NUM> that corresponds to a position of the localised feature or artefact in the second image <NUM>.

If the processor <NUM> determines that the first image <NUM> has a localised feature or artefact of a greater brightness than one or more adjacent areas or regions of the first image <NUM>, which localised feature or artefact of the first image <NUM> is located at a position in the first image <NUM> that corresponds to a position of the localised feature or artefact in the second image <NUM> at step <NUM>, the method returns a negative test result at step <NUM> indicating that the camera flash <NUM> is non-operational.

If the processor <NUM> determines that the first image <NUM> does not have a localised feature or artefact of a greater brightness than one or more adjacent areas or regions of the first image <NUM>, which localised feature or artefact of the first image <NUM> is located at a position in the first image <NUM> that corresponds to a position of the localised feature or artefact in the second image <NUM> at step <NUM>, the method returns a positive test result at step <NUM> indicating that the camera flash <NUM> is operational.

If the processor <NUM> determines that the second image <NUM> does not have a localised feature or artefact of a greater brightness than one or more adjacent areas or regions of the second image <NUM>, the method returns an inconclusive test result at step <NUM>. Similarly, if at step 106c, the processor <NUM> determines for each of the one or more properties of the object <NUM>, that the determined first and second values for the property of the object <NUM> do not comply with the corresponding predetermined criterion, the processor <NUM> determines that the first and second images <NUM>, <NUM> are images of different scenes at step 106e and the processor <NUM> determines an inconclusive test result at step <NUM>.

In a first alternative to the method for determining whether the first and second images are images of the same scene of steps 106a-106e illustrated in <FIG>, the processor <NUM> determines a quantitative degree of similarity between the first and second images <NUM>, <NUM>, and the processor <NUM> determines that the first and second images <NUM>, <NUM> are images of the same scene if the quantitative degree of similarity between the first and second images <NUM>, <NUM> comply with a predetermined image similarity criterion. For example, the processor <NUM> determines that the first and second images are images of the same scene if a difference between the quantitative degree of similarity between the first and second images is less than a predetermined threshold value. More specifically, the processor <NUM> determines a cross-correlation between the first and second images <NUM>, <NUM> or a cross-correlation between corresponding portions of the first and second images <NUM>, <NUM>, and the processor <NUM> determines that the first and second images <NUM>, <NUM> are images of the same scene if the cross-correlation between the first and second images <NUM>, <NUM> complies with a predetermined cross-correlation criterion. For example, the processor <NUM> determines that the first and second images are images of the same scene if a difference between the cross-correlation between the first and second images is less than a predetermined threshold value.

In a second alternative to the method for determining whether the first and second images are images of the same scene of steps 106a-106e illustrated in <FIG>, the processor <NUM> uses the accelerometer <NUM> to measure any movements of the mobile electronic device <NUM> (and therefore also the camera <NUM>) between a time of capture of the first image <NUM> and a time of capture of the second image <NUM> and the processor <NUM> determines that the first and second images <NUM>, <NUM> are images of the same scene if the size of any movements of the camera <NUM> comply with one or more predetermined movement criteria. For example, the processor <NUM> determines that the first and second images <NUM>, <NUM> are images of the same scene if the size of any movements of the camera <NUM> are less than one or more corresponding predetermined threshold values.

In a third alternative to the method for determining whether the first and second images are images of the same scene of steps 106a-106e illustrated in <FIG>, the processor <NUM> determines a location and orientation of the mobile electronic device <NUM> (and therefore also the camera <NUM>) at the time of capture of each of the first and second images <NUM>, <NUM> from one or more signals received wirelessly by the antenna <NUM> from one or more cellular base stations and/or from one or more satellites such as one or more GPS satellites. The processor <NUM> then determines that the first and second images <NUM>, <NUM> are images of the same scene if the determined locations of the camera <NUM> at the times of capture of the first and second images <NUM>, <NUM> comply with a predetermined location criteria and the determined orientations of the camera <NUM> at the times of capture of the first and second images <NUM>, <NUM> comply with a corresponding predetermined orientation criteria. For example, the processor <NUM> determines that the first and second images <NUM>, <NUM> are images of the same scene if a difference between the determined locations of the camera <NUM> at the times of capture of the first and second images <NUM>, <NUM> is less than a corresponding predetermined location threshold value and a difference between the determined orientations of the camera <NUM> at the times of capture of the first and second images <NUM>, <NUM> is less than a corresponding predetermined orientation threshold value.

A fourth alternative to the method for determining whether the first and second images are images of the same scene of steps 106a-106e illustrated in <FIG>, is now described with reference to <FIG>. In the fourth alternative method for determining whether the first and second images are images of the same scene, the processor <NUM> identifies at step 306a an object <NUM> in the first image <NUM> and identifies the same object <NUM> in the second image <NUM>. For example, the processor <NUM> may use an image processing algorithm to identify the object <NUM> in the first image <NUM> and to identify the same object <NUM> in the second image <NUM>. The image processing algorithm may, for example, be based on a machine learning algorithm. At step 306b, the processor <NUM> determines, for each of one or more properties of the object <NUM>, a first value for the property of the object <NUM> from the first image <NUM> and a second value for the property of the object <NUM> from the second image <NUM>. The one or more properties of the object may, for example, include one or more of a size of the object <NUM>, an aspect ratio of the object <NUM>, a position of the object <NUM>, and an orientation of the object <NUM>.

The processor <NUM> then determines at step 306c whether, for each of the one or more properties of the object <NUM>, the determined first and second values of the property of the object <NUM> comply with a corresponding predetermined criterion. For example, the processor <NUM> determines, for each of the one or more properties of the object <NUM>, a difference between the determined first and second values of the property of the object <NUM>, and the processor <NUM> determines whether, for each of the one or more properties of the object <NUM>, the determined difference between the determined first and second values of the property of the object <NUM> is less than a corresponding predetermined threshold value. If at step 306c, the processor <NUM> determines that the determined first and second values of the property of the object <NUM> comply with the corresponding predetermined criterion for each of the one or more properties of the object <NUM>, the processor <NUM> determines that the first and second images <NUM>, <NUM> are images of the same scene at step 306d. If at step 306c, the processor <NUM> determines for each of the one or more properties of the object <NUM>, that the determined first and second values for the property of the object <NUM> do not comply with the corresponding predetermined criterion, the processor <NUM> determines that the first and second images <NUM>, <NUM> are images of different scenes at step 306e.

Various modifications are possible to the apparatus and methods described above with departing from the scope defined by the appended claims. For example, in an alternative method to any of the methods described with reference to <FIG> for automatically testing the operational status of the camera flash <NUM> of the mobile electronic device <NUM>, the mobile electronic device <NUM> may enable the camera flash <NUM> and prompt a user of the mobile electronic device <NUM> to use the camera <NUM> to capture a first image of a scene. This alternative method may continue with the mobile electronic device <NUM> disabling the camera flash <NUM> and prompting the user to use the camera <NUM> to capture a second image of the same scene. It is an advantage of this alternative method that any technical limitations preventing normal operation of the camera flash <NUM> may be detected before capturing any images. Such technical limitations may include low charge of a battery of the mobile electronic device <NUM> or any restrictions set on the use of the camera flash <NUM> by the diagnostics application <NUM>, for example.

Claim 1:
A method for use in testing an operational status of a light source (<NUM>) for illuminating a scene, the light source (<NUM>) having a fixed spatial relationship relative to a camera (<NUM>), and the method comprising:
using the camera (<NUM>) to capture a first image (<NUM>) when the light source (<NUM>) is disabled;
using the camera (<NUM>) to capture a second image (<NUM>) when the light source (<NUM>) is enabled; and
determining a test result indicating the operational status of the light source (<NUM>) based at least in part on:
a light source setting when the camera (<NUM>) captures each of the first and second images (<NUM>, <NUM>), the light source setting indicating whether the light source (<NUM>) is disabled or enabled when the camera (<NUM>) captures the first and second images (<NUM>, <NUM>) ;
at least one of:
one or more camera settings when the camera (<NUM>) captures the first and second images (<NUM>, <NUM>); and
one or more image properties of the first and second images (<NUM>, <NUM>); and characterized in that the method further comprises the step of determining whether the first and second images (<NUM>, <NUM>) are images of the same scene.