Abstract: Laundry treatment appliances for use in a typical household include a tub that has an opening to provide access to the interior and at least partially defines a treating chamber into which fabric items such as clothes, towels, or linens can be placed to undergo a washing operation. A system can be provided for recirculating wash liquid through the tub to reduce water consumption. At least one tank or reservoir and a coagulant dosing system can be included for the chemical treatment of wash water as part of the wash liquid recirculation system. The tank can also serve to separate coagulated solids from the wash water.

Abstract: Laundry treatment appliances for use in a typical household include a tub that has an opening to provide access to the interior and at least partially defines a treating chamber into which fabric items such as clothes, towels, or linens can be placed to undergo a washing operation. A system can be provided for recirculating wash liquid through the tub to reduce water consumption. At least one tank or reservoir and a coagulant dosing system can be included for the chemical treatment of wash water as part of the wash liquid recirculation system. The tank can also serve to separate coagulated solids from the wash water.

Abstract: A system processes a set of images to verify whether the images depict a type of property damage, such as hail damage from a hail storm. The system receives digital images of a roof or other facet of the property that were taken by an image capturing device after the storm event. The system also receives storm data relating to the storm event and claim data related to a property damage claim. The system uses the claim data to process the digital images to automatically identify damage to the roof or other facet. The system then analyzes the storm data to determine whether the damage is consistent with an actual, naturally-occurring storm event, and it generates a report depicting its findings.

Abstract: A system segments a set of images of a property to identify a type of damage to the property. The system receives, from an image capturing device, a digital image of a roof or other feature of the property. The system processes the image to identify a set of segments, in which each segment corresponds to a piece of the feature, such as a tab or tooth of a shingle on the roof. The system saves a result of the processing to a data file as a segmented image of the property, and it uses the segmented image to identify a type of damage to the property.

Abstract: A system estimates quality of a digital image by accessing a corpus of digital images of one or more subjects, such as a facet of a property. The system will receive, for at least a subset of the corpus, an indicator that one or more patches of each image in the subset is out of focus. The system will train a classifier by obtaining a feature representation of each pixel in each image, along with a focus value that represents an extent to which each pixel in the image is in focus or out of focus. The system will use the classifier to analyze pixels of a new digital image and assess whether each analyzed pixel in the new digital image is in focus or out of focus. The system may use the image to assess whether an incident occurred, such as storm-related damage to the property.

Abstract: A system for assessing a property damage claim uses an imaging device to capture images of a property that has reportedly been damaged by an incident. The system receives a property damage incident type, along with image processing criteria for processing images that are associated with the incident type. The system automatically processes the images according to the image processing criteria to identify one or more characteristics in the images and, based on the identified characteristics, determines whether certain claim processing criteria are satisfied. The claim processing criteria may help the system determine whether the property actually was damaged by the reported incident. The system will generate a command to process the property damage claim only if the system determines that one or more images show that the claim processing criteria are satisfied.

Abstract: A system estimates quality of a digital image by accessing a corpus of digital images of one or more subjects, such as a facet of a property. The system will receive, for at least a subset of the corpus, an indicator that one or more patches of each image in the subset is out of focus. The system will train a classifier by obtaining a feature representation of each pixel in each image, along with a focus value that represents an extent to which each pixel in the image is in focus or out of focus. The system will use the classifier to analyze pixels of a new digital image and assess whether each analyzed pixel in the new digital image is in focus or out of focus. The system may use the image to assess whether an incident occurred, such as storm-related damage to the property.

Abstract: A system estimates quality of a digital image by accessing a corpus of digital images of one or more subjects, such as a facet of a property. The system will receive, for at least a subset of the corpus, an indicator that one or more patches of each image in the subset is out of focus. The system will train a classifier by obtaining a feature representation of each pixel in each image, along with a focus value that represents an extent to which each pixel in the image is in focus or out of focus. The system will use the classifier to analyze pixels of a new digital image and assess whether each analyzed pixel in the new digital image is in focus or out of focus. The system may use the image to assess whether an incident occurred, such as storm-related damage to the property.

Abstract: A system for capturing property damage images includes an imaging device and a knowledge base of property damage incident types. The knowledge base also includes, for each category, one or more image acquisition parameters that are associated with the category. A processor receives a property damage incident type for a property damage claim that is associated with a property that reportedly experienced an incident, retrieves from the knowledge base one or more image acquisition parameters that are associated with the received incident type, and uses the one or more applicable image acquisition parameters to automatically cause the imaging device to capture digital images of the property using the retrieved one or more image acquisition parameters.

Abstract: A system segments a set of images of a property to identify a type of damage to the property. The system receives, from an image capturing device, a digital image of a roof or other feature of the property. The system processes the image to identify a set of segments, in which each segment corresponds to a piece of the feature, such as a tab or tooth of a shingle on the roof. The system saves a result of the processing to a data file as a segmented image of the property, and it uses the segmented image to identify a type of damage to the property.

Abstract: A system processes a set of images to verify whether the images depict a type of property damage, such as hail damage from a hail storm. The system receives digital images of a roof or other facet of the property that were taken by an image capturing device after the storm event. The system also receives storm data relating to the storm event and claim data related to a property damage claim. The system uses the claim data to process the digital images to automatically identify damage to the roof or other facet. The system then analyzes the storm data to determine whether the damage is consistent with an actual, naturally-occurring storm event, and it generates a report depicting its findings.

Abstract: A system estimates quality of a digital image by accessing a corpus of digital images of one or more subjects, such as a facet of a property. The system will receive, for at least a subset of the corpus, an indicator that one or more patches of each image in the subset is out of focus. The system will train a classifier by obtaining a feature representation of each pixel in each image, along with a focus value that represents an extent to which each pixel in the image is in focus or out of focus. The system will use the classifier to analyze pixels of a new digital image and assess whether each analyzed pixel in the new digital image is in focus or out of focus. The system may use the image to assess whether an incident occurred, such as storm-related damage to the property.

Abstract: A system for assessing a property damage claim uses an imaging device to capture images of a property that has reportedly been damaged by an incident. The system receives a property damage incident type, along with image processing criteria for processing images that are associated with the incident type. The system automatically processes the images according to the image processing criteria to identify one or more characteristics in the images and, based on the identified characteristics, determines whether certain claim processing criteria are satisfied. The claim processing criteria may help the system determine whether the property actually was damaged by the reported incident. The system will generate a command to process the property damage claim only if the system determines that one or more images show that the claim processing criteria are satisfied.

Abstract: A system for capturing property damage images includes an imaging device and a knowledge base of property damage incident types. The knowledge base also includes, for each category, one or more image acquisition parameters that are associated with the category. A processor receives a property damage incident type for a property damage claim that is associated with a property that reportedly experienced an incident, retrieves from the knowledge base one or more image acquisition parameters that are associated with the received incident type, and uses the one or more applicable image acquisition parameters to automatically cause the imaging device to capture digital images of the property using the retrieved one or more image acquisition parameters.

Abstract: A video-based teaching aid system and method. Video images are recorded of at least some of a plurality of people in a classroom setting by use of a video camera arrangement. Expressions of the people in the video images are identified by use of an expression recognition module configured to receive the video images from the video camera arrangement. The identified expressions of the people in the video images are correlated with at least one of an event or an outcome of an event occurring in a classroom setting by use of a correlation module. The results of the correlating are outputted by an output device.

Abstract: Methods, devices, and systems replace solid lines of user-fillable areas of a print job with patterned lines and then print the print job with the patterned lines to print user-fillable pre-printed forms, using a printing device. These methods, devices, and systems also scan at least one of the user-fillable pre-printed forms having user markings to produce a scan, using an optical scanner. Further, such methods, devices, and systems produce an altered scan by removing only the patterned lines from the scan to leave the user markings in the altered scan using the image processor. Then, these methods, devices, and systems can identify user-supplied characters by performing automated character recognition on the user markings in the altered scan using the image processor and output such user-supplied characters from the image processor.

Abstract: Methods, devices, and systems replace solid lines of user-fillable areas of a print job with patterned lines and then print the print job with the patterned lines to print user-fillable pre-printed forms, using a printing device. These methods, devices, and systems also scan at least one of the user-fillable pre-printed forms having user markings to produce a scan, using an optical scanner. Further, such methods, devices, and systems produce an altered scan by removing only the patterned lines from the scan to leave the user markings in the altered scan using the image processor. Then, these methods, devices, and systems can identify user-supplied characters by performing automated character recognition on the user markings in the altered scan using the image processor and output such user-supplied characters from the image processor.

Abstract: A video-based teaching aid system and method. Video images are recorded of at least some of a plurality of people in a classroom setting by use of a video camera arrangement. Expressions of the people in the video images are identified by use of an expression recognition module configured to receive the video images from the video camera arrangement. The identified expressions of the people in the video images are correlated with at least one of an event or an outcome of an event occurring in a classroom setting by use of a correlation module. The results of the correlating are outputted by an output device.

Abstract: An apparatus (100) and method (200) that senses photoreceptor failure in a xerographic printing apparatus is disclosed. The xerographic printing apparatus can include a rotatable photoreceptor (110) having a photoreceptor surface (111), a cleaning device (124) for removing marking material from the photoreceptor, and a printing apparatus controller (150) that controls operations of the xerographic printing apparatus. The method can include charging (220) the photoreceptor surface to a fixed voltage. The method can include discharging (230) at least a portion of the charged photoreceptor surface to an exposed voltage. The method can include developing (240) the discharged portion of the photoreceptor surface by providing a cleaning field between the charged photoreceptor surface fixed voltage and a developing bias voltage. The method can include reducing (250) the cleaning field. The method can include generating (260) a developed image on the photoreceptor using the reduced cleaning field.

Abstract: An apparatus (100) and method (200) that senses photoreceptor failure in a xerographic printing apparatus is disclosed. The xerographic printing apparatus can include a rotatable photoreceptor (110) having a photoreceptor surface (111), a cleaning device (124) for removing marking material from the photoreceptor, and a printing apparatus controller (150) that controls operations of the xerographic printing apparatus. The method can include charging (220) the photoreceptor surface to a fixed voltage. The method can include discharging (230) at least a portion of the charged photoreceptor surface to an exposed voltage. The method can include developing (240) the discharged portion of the photoreceptor surface by providing a cleaning field between the charged photoreceptor surface fixed voltage and a developing bias voltage. The method can include reducing (250) the cleaning field. The method can include generating (260) a developed image on the photoreceptor using the reduced cleaning field.