A system for organizing digital files is provided, wherein tagging data is applied to a sequence of files. A tagging image having tagging data therein is preferably provided before or after the sequence, or both. A text recognizing technology may be used to extract the tagging data from a tagging image. For example, if a tagging image is taken on a camera prior to a sequence of images, the system may extract tagging data from the tagging image and apply such tagging data to the sequence of image files. Preferably, the system provides for renaming of the image files utilizing the tagging data.

Systems and methods for discriminating between malignant and benign pigmented skin lesions based on optical analysis using spatial distribution maps, morphological parameters, and additional diagnostic parameters derived from images of tissue lesions. A handheld optical transfer diagnosis device is disclosed capable of capturing a series of reflectance images of a skin lesion at a variety of angles of illumination and observation.

This invention relates to creating a narrative description of media content. In an embodiment, a computer-implemented method describes content of a group of images. The group of images includes a first image and a second image. A first object in the first image is recognized to determine a first content data. A second object in the second image is recognized to determine a second content data. Finally, a narrative description of the group of images is determined according to a parameterized template and the first and second content data.

In one embodiment, a set of tags that has been generated by performing computer vision analysis of image content of a visual media item may be obtained, where each tag of the set of tags has a corresponding probability. In addition, a set of information that is independent from the image content of the visual media item may be obtained. The probability of at least a portion of the set of tags may be modified based, at least in part, upon the set of information.

Systems and method are provided for controlling an autonomous vehicle. A camera configured to capture an image, and a controller can execute an autonomous driving system (ADS) that classify that image. The ADS comprises a classification system for classifying objects in an environment within a driveable area of the autonomous vehicle. The classification system comprises a processor configured to execute a region proposal generator module and an image classification module. The region proposal generator module generates a set of bounding box region proposals for the image. The bounding box region proposals are selected areas of the image that include objects to be classified. The image classification module classifies, via a neural network executed by the processor, the objects from the image that are within one of the bounding box region proposals

A quality of an image obtained by image processing is improved with a shorter amount of time spent in the image processing. An image processing apparatus includes, an acquisition unit configured to acquire an image, a determination unit configured to determine a quality of the acquired image, a switching unit configured to switch between settings of acquiring and not acquiring a reference image, from a communication apparatus connected to the image processing apparatus, used for improving the quality of the acquired image, based on the determined quality, and a processing unit configured to perform image processing by using the reference image acquired from the communication apparatus, in accordance with the switching by the switching unit.

Systems, processes, and computer program products for creating visual designs and arrangements that originate from an image or images are provided. In particular, the present subject matter relates to systems, processes, and computer program products for taking captured images of an intended operating environment and creating visual designs that create visual confusion that can be utilized to disguise a recognizable form of a person or an object by breaking up its outline using portions, magnifications and distortions of a single captured image, portions, magnifications and distortions of multiple captured images, and/or disruptive patterns that can projected on an image screen or can be printed on a material.

Approaches are described for managing the processing of image or video data captured by a portable computing device. The device provides a set of images to a remote server executing “in the cloud”. The set of images can include a reference image and at least one other image captured subsequent or prior to the reference. Upon receiving the set of images at the remote server operating, the remote server can process the images to determine a similarity between the reference image and each of the other images. Thereafter, each image having a similarity value above a similarity value threshold can be aligned with the reference image, and the pixel values for corresponding locations in each of the images can be combined to create a processed image. The processed images can be provided to the computing device from the remote server, where the user can decide to accept or discard the image.

An image pipeline execution method includes analyzing at least one attribute of an image and determining an image type of the image from a set of predetermined image types based on the analyzing the at least one attribute of the image. The image pipeline execution method also includes dynamically establishing an image pipeline to process the image based on the image type and executing the image pipeline to print the image.

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for an active lighting system. In one aspect, a method includes receiving a first image of the physical document having a first glare signature and a second image of the physical document having a second glare signature that is different from the first glare signature; determining a first glare map of the first image and a second glare map of the second image; comparing the first glare map to the second glare map; and generating the digital image based on the comparison of the first and second glare maps.