Abstract: Apparatuses, systems, and methods for object recognition and presentation are provided. An example apparatus may include a camera, an assistance feedback device, an input device, and processing circuitry. The processing circuitry may be configured receive an image from the camera, compare characteristic features within the image to an object identification dataset to identify object matches for a plurality of objects within the image, receive a selected name of an identified object from the user via the input device, and transmit assistance feedback to the user indicating a position of the selected object within the field of view via the assistance feedback device.

Abstract: Apparatuses, systems, and methods for object recognition and presentation are provided. An example apparatus may include a camera, an assistance feedback device, an input device, and processing circuitry. The processing circuitry may be configured receive an image from the camera, compare characteristic features within the image to an object identification dataset to identify object matches for a plurality of objects within the image, receive a selected name of an identified object from the user via the input device, and transmit assistance feedback to the user indicating a position of the selected object within the field of view via the assistance feedback device.

Abstract: Apparatuses, systems, and methods for object recognition and presentation are provided. An example apparatus may include a camera, an assistance feedback device, an input device, and processing circuitry. The processing circuitry may be configured receive an image from the camera, compare characteristic features within the image to an object identification dataset to identify object matches for a plurality of objects within the image, receive a selected name of an identified object from the user via the input device, and transmit assistance feedback to the user indicating a position of the selected object within the field of view via the assistance feedback device.

Abstract: Apparatuses, systems, and methods for object recognition and presentation are provided. An example apparatus may include a camera, an assistance feedback device, an input device, and processing circuitry. The processing circuitry may be configured receive an image from the camera, compare characteristic features within the image to an object identification dataset to identify object matches for a plurality of objects within the image, receive a selected name of an identified object from the user via the input device, and transmit assistance feedback to the user indicating a position of the selected object within the field of view via the assistance feedback device.

Abstract: The Digital Video Authenticator (DVA) addresses law enforcement concerns for a means to authenticate digital video (DV) so that it will be admissible and trusted as evidence in court. The DVA is a peripheral device attached to a commercial digital video recording device whose purpose is to generate and record authentication data simultaneously as DV is recorded by the video recording device. Verification of the authenticity of a DV sample will be accomplished using non-real-time software tools. The DVA system and method reads digital video (DV) data from a digital video recording device; parses the DV data into elements representing video, audio, control and timing data; and creates digital signatures that can be used to validate the original DV tape. The combination of secure digital signatures and repeatability of the DV data stored on tape provides the basis for proving the original video has not been modified.

Abstract: A system and method of automatically creating a NIMA certified line drawing from a National Imagery Transmission Format (NITF) image file. A grayscale (electro-optical) image and its associated metadata from a NITF file is input into the computer based system. Pre-screening operations are performed on the metadata prior to image processing to ensure that National Imagery and Mapping Agency (NIMA) requirements and criteria are met. Image processing algorithms then perform filtering, encoding, edge detection, and custom edge pattern classification procedures to create a declassified line drawing. The line drawing can then be saved in any number of standard commercial file formats.

Abstract: The Digital Video Authenticator (DVA) addresses law enforcement concerns for a means to authenticate digital video (DV) so that it will be admissible and trusted as evidence in court. The DVA is a peripheral device attached to a commercial digital video recording device whose purpose is to generate and record authentication data simultaneously as DV is recorded by the video recording device. Verification of the authenticity of a DV sample will be accomplished using non-real-time software tools. The DVA system and method reads digital video (DV) data from a digital video recording device; parses the DV data into elements representing video, audio, control and timing data; and creates digital signatures that can be used to validate the original DV tape. The combination of secure digital signatures and repeatability of the DV data stored on tape provides the basis for proving the original video has not been modified.

Abstract: A system and method of automatically creating a NIMA certified line drawing from a National Imagery Transmission Format (NITF) image file. A grayscale (electro-optical) image and its associated metadata from a NITF file is input into the computer based system. Pre-screening operations are performed on the metadata prior to image processing to ensure that National Imagery and Mapping Agency (NIMA) requirements and criteria are met. Image processing algorithms then perform filtering, encoding, edge detection, and custom edge pattern classification procedures to create a declassified line drawing. The line drawing can then be saved in any number of standard commercial file formats.