G06K15/1886

Context-aware image compression

In one embodiment, an apparatus comprises a storage device and a processor. The storage device may store a plurality of compressed images comprising one or more compressed master images and one or more compressed slave images. The processor may: identify an uncompressed image; access context information associated with the uncompressed image and the one or more compressed master images; determine, based on the context information, whether the uncompressed image is associated with a corresponding master image; upon a determination that the uncompressed image is associated with the corresponding master image, compress the uncompressed image into a corresponding compressed image with reference to the corresponding master image; upon a determination that the uncompressed image is not associated with the corresponding master image, compress the uncompressed image into the corresponding compressed image without reference to the one or more compressed master images; and store the corresponding compressed image on the storage device.

Image processing apparatus, image processing method, non-transitory computer-readable storage medium storing program
11797806 · 2023-10-24 · ·

An image processing apparatus with a processor and a memory storing instructions, that, when executed, cause the processor to obtain HDR data representing a high-dynamic range (HDR) image, in an image transfer function of the HDR data, a tone of each pixel is defined based on a relative luminance value, to obtain print information to perform printing based on the obtained HDR data, to set luminance information to be a target absolute luminance value, and to perform a luminance conversion on the HDR data so that a tone of each pixel is defined based on an absolute luminance value and the target absolute luminance value being a maximum luminance, to convert a dynamic range of luminance of the HDR data, on which the luminance conversion has been performed, into a dynamic range corresponding to printing of an image on a print medium performed based on the print information.

Cascade convolutional neural network

In one embodiment, an apparatus comprises a communication interface and a processor. The communication interface is to communicate with a plurality of devices. The processor is to: receive compressed data from a first device, wherein the compressed data is associated with visual data captured by sensor(s); perform a current stage of processing on the compressed data using a current CNN, wherein the current stage of processing corresponds to one of a plurality of processing stages associated with the visual data, and wherein the current CNN corresponds to one of a plurality of CNNs associated with the plurality of processing stages; obtain an output associated with the current stage of processing; determine, based on the output, whether processing associated with the visual data is complete; if the processing is complete, output a result associated with the visual data; if the processing is incomplete, transmit the compressed data to a second device.

Algorithm management blockchain
11481583 · 2022-10-25 · ·

In one embodiment, an apparatus comprises a communication interface, a memory, and a processor. The communication interface is to communicate with one or more devices. The memory to store a device identity blockchain. The processor is to: receive a device identity transaction from a first device, wherein the device identity transaction comprises a device identity; compute a hash of the device identity; determine, based on the hash, whether the device identity is registered in the device identity blockchain; and upon a determination that the device identity is not registered in the device identity blockchain, add the device identity transaction to the device identity blockchain.

Analytic image format for visual computing

In one embodiment, an apparatus comprises a storage device and a processor. The storage device stores a plurality of images captured by a camera. The processor: accesses visual data associated with an image captured by the camera; determines a tile size parameter for partitioning the visual data into a plurality of tiles; partitions the visual data into the plurality of tiles based on the tile size parameter, wherein the plurality of tiles corresponds to a plurality of regions within the image; compresses the plurality of tiles into a plurality of compressed tiles, wherein each tile is compressed independently; generates a tile-based representation of the image, wherein the tile-based representation comprises an array of the plurality of compressed tiles; and stores the tile-based representation of the image on the storage device.

IMAGE FORMING APPARATUS AND METHOD OF CONTROLLING IMAGE FORMING APPARATUS
20220300215 · 2022-09-22 ·

An image forming apparatus includes a sensor configured to detect an original, a nonvolatile storage that includes a semiconductor area, a setting unit configured to execute a setting for dividing the semiconductor area into a plurality of areas, and a controller configured to execute Trim processing on the divided areas in response to passing of a predetermined time period while the image forming apparatus is in a standby state. The controller is configured to stop the Trim processing based on a detection of the original detected by the sensor while the Trim processing is executed.

Image forming apparatus and method of controlling image forming apparatus for executing notification processing of notifying a storage of an area
11379165 · 2022-07-05 · ·

An image forming apparatus includes a sensor configured to detect an original, a nonvolatile storage that includes a semiconductor area, a setting unit configured to execute a setting for dividing the semiconductor area into a plurality of areas, and a controller configured to execute Trim processing on the divided areas in response to passing of a predetermined time period while the image forming apparatus is in a standby state. The controller is configured to stop the Trim processing based on a detection of the original detected by the sensor while the Trim processing is executed.

IMAGE FORMING APPARATUS
20220292320 · 2022-09-15 · ·

According to at least one embodiment, an image forming apparatus includes a processor configured to cause forming an image with a decolorable color material on a tagged paper sheet with an RFID tag, reading data of the RFID tag attached to the tagged paper sheet before the image is formed, and promoting information related to reuse of the tagged paper sheet based on the data read from the RFID tag before the image is formed on the tagged paper sheet.

Printing control apparatus, printing method, and printing control program
11281948 · 2022-03-22 · ·

A printing control apparatus includes a control unit. Provided that n is an integer equal to or greater than one, the control unit configured to perform printing control processing including a plurality of types of processing configured to be performed simultaneously is configured to, in the printing control processing performed for an n-th time, write, to a first storage medium of the storage unit, n-th print data that is the print data generated in the printing control processing performed for an n-th time, and, in the printing control processing performed for an n+1-th time, write, to a second storage medium of the storage unit, n+1-th print data that is the print data generated in the printing control processing performed for an n+1-th time, and also read the n-th print data from the first storage medium and supply the n-th print data to the printing unit.

Frequency-domain convolutional neural network

In one embodiment, an apparatus comprises a memory and a processor. The memory is to store visual data associated with a visual representation captured by one or more sensors. The processor is to: obtain the visual data associated with the visual representation captured by the one or more sensors, wherein the visual data comprises uncompressed visual data or compressed visual data; process the visual data using a convolutional neural network (CNN), wherein the CNN comprises a plurality of layers, wherein the plurality of layers comprises a plurality of filters, and wherein the plurality of filters comprises one or more pixel-domain filters to perform processing associated with uncompressed data and one or more compressed-domain filters to perform processing associated with compressed data; and classify the visual data based on an output of the CNN.