A page orientation component of an image processing device receives an image of a document, transforms the image to a binarized image by performing a binarization operation on the image, and identifies a portion of the binarized image that comprises one or more rows of textual content. The page orientation component identifies a plurality of horizontal runs of white pixels and a plurality of vertical runs of white pixels in the one or more rows of textual content in the portion of the binarized image. The page orientation component generates a first histogram for the plurality of horizontal runs of white pixels, and a second histogram for the plurality of vertical runs of white pixels, and determines an orientation of the one or more rows of textual content in the image based on the first histogram and the second histogram.

Systems and methods for performing three-dimensional semantic parsing of indoor spaces in accordance with embodiments of the invention are disclosed. In one embodiment, a method includes receiving input data representing a three-dimensional space, determining disjointed spaces within the received data by generating a density histogram on each of a plurality of axes, determining space dividers based on the generated density histogram, and dividing the point cloud data into segments based on the determined space dividers, and determining elements in the disjointed spaces by aligning the disjointed spaces within the point cloud data along similar axes to create aligned versions of the disjointed spaces normalizing the aligned version of the disjointed spaces into the aligned version of the disjointed spaces, determining features in the disjointed spaces, generating at least one detection score, and filtering the at least one detection score to determine a final set of determined elements.

Techniques for processing an image of a check captured using a mobile device are provided. The check image is processed to determine whether the check can be deposited at a bank via a mobile deposit process. The system can identify regions of the check—such as the endorsement area—to determine if the check has been properly endorsed. The system can be implemented on a mobile device and/or a server, where the mobile device routes the check image to the server for processing. If the check cannot be deposited, a rejection is forwarded in real time to the mobile device for possible correction.

There is described herein a method and system for detecting, in a segmented image, the presence and position of objects with a dimension greater than or equal to a minimum dimension. The objects exhibit a property whereby a distance map of the object at a first scale and a distance map of the object at a second scale greater than the first scale differ by a constant value over a domain of the distance map of the object at the first scale. A distance map of a model object is compared to a distance map of a target object using a similarity score that is invariant to an offset.

This disclosure describes methods, techniques, devices, and apparatuses for graphics and display processing for light field projection displays. In some examples, this disclosure describes a projection display system capable of rendering and displaying multiple annotations at the same time. An annotation is any information (e.g., texts, signs, directions, logos, phone numbers, etc.) that may be displayed. In one example, this disclosure proposes techniques for rendering and displaying multiple annotations at the same time at multiple different focal lengths.

The disclosure relates to a non-transitory computer-readable storage medium storing computer program instructions which, when executed by a processor, cause the processor to process image data defining an image of a retina to determine a location of an anatomical feature of the retina in the image by receiving the image data; calculating, for each of a plurality of pixels of the image data, a respective local orientation vector indicative of the orientation of any blood vessel present in the image; calculating a normalised local orientation vector for each of the plurality of pixels; operating on an array of accumulators, wherein each accumulator in the array is associated with a respective pixel of the image data; and determining the location of the anatomical feature in the image of the retina using the location of a pixel of the image data which is associated with an accumulator having accumulated an accumulated value.

In an example embodiment, a deep convolutional neural network (DCNN) is created to assign a professionalism score to an input image. The professionalism score indicates a perceived professionalism of a subject of the input image. The DCNN is designed to automatically learn features of images relevant to the professionalism through a training process.

Described is a system for object detection in images or videos using spiking neural networks. An intensity saliency map is generated from an intensity of an input image having color components using a spiking neural network. Additionally, a color saliency map is generated from a plurality of colors in the input image using a spiking neural network. An object detection model is generated by combining the intensity saliency map and multiple color saliency maps. The object detection model is used to detect multiple objects of interest in the input image.

According to an embodiment, an image processing method is implemented in an imaging device that includes a microlens array including microlenses, a main lens configured to guide light from a photographic subject to the microlens array, and an image sensor configured to receive the light after passing through the main lens and the microlens array. The method includes: obtaining an image captured by the image sensor; setting, according to an image height, an arrangement of a microlens image of interest and comparison-target microlens images from among microlens images that are included in the image and that are formed by the microlenses; detecting an amount of image shift between the microlens image of interest and each of the comparison-target microlens images by comparing the microlens image of interest with the comparison-target microlens images; and calculating a distance corresponding to the microlens image of interest using the amounts of image shift.

Disclosed are various embodiments for improving optical character recognition approaches through the use of gap shifting. A text detection process is performed upon an image to detect a first region of text. A second region that is in line with the first region is shifted to reduce a gap between the first region and the second region, thereby creating a modified image. The text detection process is performed upon the modified image in order to detect text within the second region.