Abstract: A class labeling system for autonomous driving includes a detection module, a segmentation module, and a lane road boundary detection module. The detection module is configured to detect objects for autonomous driving from an image captured by a camera to generate a bounding box for each of the objects and detect property information about the object. The segmentation module is configured to determine classes for each pixel of the bounding box detected by the detection module and process at least one of the classes as don't care. The lane road boundary detection module is configured to detect at least one of lane and road boundaries using the bounding box detected by the detection module.

Abstract: An automatic image synthesizing apparatus including an image search unit configured to search for and extract a frame image having an object to be learned or replaced from a plurality of frame images inputted through a vehicle camera; an instance object detection unit configured to detect an instance object to be learned or replaced from the extracted frame image; an image extraction and object class information detection unit configured to extract mask-segmented objects from the extracted frame image and form a data-structure; a standard image mapping unit configured to map a standard image matching a class value of the mask-segmented object; and a generative adversarial network (GAN) network unit configured to receive the selected standard image and the mask segmentation image and learn a replacement image or produce a replacement image based on a learning result.

Abstract: Provided is a data processing device and a method of operating the same. The data processing device includes: a plurality of preprocessors configured to perform correction processing on a plurality of sensor data; a first switching circuit configured to selectively map and input the plurality of sensor data from at least two sensors to at least two preprocessors among the plurality of preprocessors; and a hybrid data processing engine configured to perform at least one of image enhancement and depth information determination on the plurality of sensor data received, via an on-the-fly method, from the at least two preprocessors.

Abstract: A class labeling system for autonomous driving includes a detection module, a segmentation module, and a lane road boundary detection module. The detection module is configured to detect objects for autonomous driving from an image captured by a camera to generate a bounding box for each of the objects and detect property information about the object. The segmentation module is configured to determine classes for each pixel of the bounding box detected by the detection module and process at least one of the classes as don't care. The lane road boundary detection module is configured to detect at least one of lane and road boundaries using the bounding box detected by the detection module.

Abstract: An automatic image synthesizing apparatus including an image search unit configured to search for and extract a frame image having an object to be learned or replaced from a plurality of frame images inputted through a vehicle camera; an instance object detection unit configured to detect an instance object to be learned or replaced from the extracted frame image; an image extraction and object class information detection unit configured to extract mask-segmented objects from the extracted frame image and form a data-structure; a standard image mapping unit configured to map a standard image matching a class value of the mask-segmented object; and a generative adversarial network (GAN) network unit configured to receive the selected standard image and the mask segmentation image and learn a replacement image or produce a replacement image based on a learning result.

Abstract: Provided is a data processing device and a method of operating the same. The data processing device includes: a plurality of preprocessors configured to perform correction processing on a plurality of sensor data; a first switching circuit configured to selectively map and input the plurality of sensor data from at least two sensors to at least two preprocessors among the plurality of preprocessors; and a hybrid data processing engine configured to perform at least one of image enhancement and depth information determination on the plurality of sensor data received, via an on-the-fly method, from the at least two preprocessors.

Abstract: Provided is a data processing device and a method of operating the same. The data processing device includes: a plurality of preprocessors configured to perform correction processing on a plurality of sensor data; a first switching circuit configured to selectively map and input the plurality of sensor data from at least two sensors to at least two preprocessors among the plurality of preprocessors; and a hybrid data processing engine configured to perform at least one of image enhancement and depth information determination on the plurality of sensor data received, via an on-the-fly method, from the at least two preprocessors.

Abstract: An image sensing device includes a single-color image sensor and a multi-color image sensor having resolutions different from each other; image data receiving circuitry configured to receive first image data from the single-color image sensor and second image data from the multi-color image sensor; first preprocessor circuitry configured to generate first aligned image data and second aligned image data based on the first image data and the second image data, respectively, by correcting an optical path difference between a pixel stream of the first image data and a pixel stream of the second image; and second preprocessor circuitry configured to generate third image data by merging the first aligned image data and the second aligned image data.

Abstract: Provided is a data processing device and a method of operating the same. The data processing device includes: a plurality of preprocessors configured to perform correction processing on a plurality of sensor data; a first switching circuit configured to selectively map and input the plurality of sensor data from at least two sensors to at least two preprocessors among the plurality of preprocessors; and a hybrid data processing engine configured to perform at least one of image enhancement and depth information determination on the plurality of sensor data received, via an on-the-fly method, from the at least two preprocessors.

Abstract: Provided is a data processing device and a method of operating the same. The data processing device includes: a plurality of preprocessors configured to perform correction processing on a plurality of sensor data; a first switching circuit configured to selectively map and input the plurality of sensor data from at least two sensors to at least two preprocessors among the plurality of preprocessors; and a hybrid data processing engine configured to perform at least one of image enhancement and depth information determination on the plurality of sensor data received, via an on-the-fly method, from the at least two preprocessors.

Abstract: An image sensing device includes a single-color image sensor and a multi-color image sensor having resolutions different from each other; image data receiving circuitry configured to receive first image data from the single-color image sensor and second image data from the multi-color image sensor; first preprocessor circuitry configured to generate first aligned image data and second aligned image data based on the first image data and the second image data, respectively, by correcting an optical path difference between a pixel stream of the first image data and a pixel stream of the second image; and second preprocessor circuitry configured to generate third image data by merging the first aligned image data and the second aligned image data.

Abstract: Provided is a data processing device and a method of operating the same. The data processing device includes: a plurality of preprocessors configured to perform correction processing on a plurality of sensor data; a first switching circuit configured to selectively map and input the plurality of sensor data from at least two sensors to at least two preprocessors among the plurality of preprocessors; and a hybrid data processing engine configured to perform at least one of image enhancement and depth information determination on the plurality of sensor data received, via an on-the-fly method, from the at least two preprocessors.

Abstract: A system-on-a-chip (SOC) that is able to randomly access target data of a video/image includes a JPEG decoder, a graphic processing unit (GPU) and a central processing unit (CPU). The JPEG decoder receives an input stream having a sequentially accessible first compression format, decodes the input stream to generate first data, and encodes the first data to generate an output stream having a randomly accessible second compression format. The GPU receives the output stream and performs graphic processing on the output stream. Therefore, the SOC readily performs graphic processing by repeatedly receiving video/image data in a short time from a storage unit in which the data is stored using a randomly accessible compression format.

Abstract: A method is for processing a Bayer domain signal of an image sensor to model an integrated noise in the image sensor. The method includes receiving the Bayer domain signal of the image signal, setting a plurality of noise models using the Bayer domain signal, and determining an integrated noise level in the image sensor based on the plurality of noise models. The noise models include a dark-current noise model, a shot noise model and a fixed-pattern noise model.

Abstract: A method is for processing a Bayer domain signal of an image sensor to model an integrated noise in the image sensor. The method includes receiving the Bayer domain signal of the image signal, setting a plurality of noise models using the Bayer domain signal, and determining an integrated noise level in the image sensor based on the plurality of noise models. The noise models include a dark-current noise model, a shot noise model and a fixed-pattern noise model.

Abstract: Provided are an apparatus and method of transmitting working context, which can minimize power consumption in a power-off standby mode of a portable apparatus including a system on a chip, where the method includes selecting a power-off standby mode, transmitting working context with respect to a hardware module, which is mounted on a semiconductor chip, to a predetermined memory, and storing the working context in the predetermined memory, transmitting the working context stored in the memory to a non-volatile memory outside the semiconductor chip, and storing the working context in the non-volatile memory, and executing the power-off standby mode; where the method may further include releasing the power-off standby mode, restoring the working context with respect to the hardware module, which is stored in the non-volatile memory, to the predetermined memory, and recovering the at least one hardware module to a state existing immediately before the power-off standby mode was executed by using the working con

Abstract: Digital logic processing devices capable of reduced power consumption may be provided. A digital logic processing device may include one or more processing elements, an input FIFO for storing data, a processing unit, and a clock controller circuit. The processing unit may process data from the input FIFO and the clock controller circuit may control a clock signal supplied to the input FIFO and the processing unit. The clock controller circuit may monitor whether there is data to be transferred to the input FIFO and states of the input FIFO and the processing unit and may control the clock signal.

Abstract: A memory controller having graphic processing function that includes a graphic processing unit operating in response to a selection signal from a master, and a memory interface for storing outputs of the graphic processing unit in an external memory at and receiving graphic data from the external memory to provide the graphic data to the graphic processing unit.

Abstract: A communication device and method is provided, comprising: a signal modulator/demodulator having a digital signal processor for effecting radio communications; and an application processor (AP) having a central processing unit and a master controller for controlling via a common bus a plurality of peripherals including an interface with the signal modulator/demodulator, wherein a memory shared by the modem and the AP is controlled via the interface. The plurality of peripherals include at least one of an image capture module, a display, and a flash memory. The master controller controls the plurality of peripherals by issuing a packetized command commonly receivable by the plurality of peripherals over the common bus, the packetized command includes a module device select signal used for selecting one of the peripherals.

Abstract: A camera interface employing a direct memory access (DMA) unit to digitally perform an image transformation such as “flipping” and “rotating” an image (e.g., to correct for X-axis, Y-axis, or XY-axes mirroring). The image transforming DMA unit includes an address generator and a data selector. The address generator appropriately modifies a frame start address, a burst transfer address, a line start address, of an image frame, based on the X, Y, or XY mirrored image mode. The data selector changes the sequences of words and of pixels in a word based upon the mirrored image mode.