Abstract: A computing device automatically determines when a user wishes to capture an image of an object in a scene via a camera of the computing device. In response, the computing device presents at a display screen an image of the scene together with an overlay template. The overlay template corresponds in shape to the object in the scene and is overlaid on the object in the scene when displayed at the display screen. The overlay template is not displayed at the display screen when the computing device does not determine that a user wishes to capture an image of an object in the scene.

Abstract: An image captured by a camera can be processed by a scanning application to identify multiple regions within the image that are suitable for scanning. These regions can be detected and selected for scanning automatically. The captured regions for the single image can be stored as individual image content files.

Abstract: A series of frames or live images received by a camera can be processed by an automatic image capture system to determine when an automatic image capture should take place. The system can detect when a scene change occurs by comparison of data for two or more frames. If a scene change is followed by a stabilization of the scene, the system can trigger an auto-capture of the stabilized scene, without the need for user input.

Abstract: An image captured by a camera can be processed by a scanning application to identify one or more regions within the image that are suitable for scanning. One or more of these regions can be selected for scanning automatically based on user-input such as a fingertip touch to a particular portion of the display screen. Users may also select multiple regions and submit multiple quadrangular regions for scanning to PDF from a single image.

Abstract: An image captured by a camera can be processed by a scanning application to identify multiple regions within the image that are suitable for scanning. These regions can be detected and selected for scanning automatically. The captured regions for the single image can be stored as individual image content files.

Abstract: A series of frames or live images received by a camera can be processed by an automatic image capture system to determine when an automatic image capture should take place. The system can detect when a scene change occurs by comparison of data for two or more frames. If a scene change is followed by a stabilization of the scene, the system can trigger an auto-capture of the stabilized scene, without the need for user input.

Abstract: A series of frames or live images received by a camera can be processed by an automatic image capture system to determine when an automatic image capture should take place. The system can detect when a scene change occurs by comparison of data for two or more frames, and for particular regions in those frames. If a scene change for the specified region is followed by a stabilization of the scene in that region, the system can trigger an auto-capture of at least the stabilized region of the scene, without the need for any user input.

Abstract: A series of frames or live images received by a camera can be processed by an automatic image capture system to determine when an automatic image capture should take place. The system can detect when a scene change occurs by comparison of data for two or more frames, and for particular regions in those frames. If a scene change for the specified region is followed by a stabilization of the scene in that region, the system can trigger an auto-capture of at least the stabilized region of the scene, without the need for any user input.

Abstract: An image captured by a camera can be processed by a scanning application to identify one or more regions within the image that are suitable for scanning. One or more of these regions can be selected for scanning automatically based on user-input such as a fingertip touch to a particular portion of the display screen. Users may also select multiple regions and submit multiple quadrangular regions for scanning to PDF from a single image.

Abstract: A video noise analyzer for detecting residual point noise in a video generates a list of candidate defective pixels by joining results of a temporal invariance detector and a spatial outlier detector. A data store is structured to contain data describing the candidate defective pixels and/or the blocks from which the pixels were selected. In other embodiments, a video noise analyzer includes a first salient analyzer structured to compare pixels within a block to a mean value of other pixels within the same block, a first threshold processor to generate a first pixel candidate list including pixels that differ significantly from their neighboring pixels, a second salient analyzer structured to generate a difference value between a subject pixel, its neighboring pixels, and neighbors of the neighboring pixels, and an identifier to label as a candidate dead pixel those pixels having a frequency occurrence of visual saliency greater than a predefined frequency threshold.

Abstract: A video noise analyzer for detecting residual point noise in a video generates a list of candidate defective pixels by joining results of a temporal invariance detector and a spatial outlier detector. A data store is structured to contain data describing the candidate defective pixels and/or the blocks from which the pixels were selected. In other embodiments, a video noise analyzer includes a first salient analyzer structured to compare pixels within a block to a mean value of other pixels within the same block, a first threshold processor to generate a first pixel candidate list including pixels that differ significantly from their neighboring pixels, a second salient analyzer structured to generate a difference value between a subject pixel, its neighboring pixels, and neighbors of the neighboring pixels, and an identifier to label as a candidate dead pixel those pixels having a frequency occurrence of visual saliency greater than a predefined frequency threshold.