A zero padding apparatus and method for fixed length signaling information are disclosed. A zero padding apparatus according to an embodiment of the present invention includes a processor configured to generate a LDPC information bit string by deciding a number of groups whose all bits are to be filled with 0 using a difference between a length of the LDPC information bit string and a length of a BCH-encoded bit string, selecting the groups using a shortening pattern order to fill all the bits of the groups with 0, and filling at least a part of remaining groups, which are not filled with 0, with the BCH-encoded bit string; and memory configured to provide the LDPC information bit string to an LDPC encoder.

Techniques are disclosed for systems and methods for water non-water segmentation of navigational imagery to assist in the autonomous navigation of mobile structures. An imagery based navigation system includes a logic device configured to communicate with an imaging module coupled to a mobile structure and/or configured to capture images of an environment about the mobile structure. The logic device may be configured to receive at least one image from the imaging module; determine a water/non-water segmented image based, at least in part, on the received at least one image, and generate a range chart corresponding to the environment about the mobile structure based, at least in part, on the determined water/non-water segmented image and/or the received at least one image.

Techniques are disclosed for systems and methods for water non-water segmentation of navigational imagery to assist in the autonomous navigation of mobile structures. An imagery based navigation system includes a logic device configured to communicate with an imaging module coupled to a mobile structure and/or configured to capture images of an environment about the mobile structure. The logic device may be configured to receive at least one image from the imaging module; determine a water/non-water segmented image based, at least in part, on the received at least one image, and generate a range chart corresponding to the environment about the mobile structure based, at least in part, on the determined water/non-water segmented image and/or the received at least one image.

A map generation device (10) generates linearization information expressing at least one or the other of a marking line of a roadway and a road shoulder edge based on measurement information of a periphery of the roadway. The measurement information is obtained by a measurement device. The map generation device (10) calculates an evaluation value expressing a reliability degree of partial information, for each partial information constituting the linearization information. A map editing device (20) displays the partial information in different modes according to the evaluation value, thereby displaying the linearization information. The map editing device (20) accepts input of editing information for the displayed linearization information.

A system for controlling a physical system via segmentation of an image includes a controller. The controller may be configured to receive an image of n pixels from a first sensor, and an annotation of the image from a second sensor, form a coupling matrix, k class vectors each of length n, and a bias coefficient based on the image and the annotation, generate n pixel vectors each of length n based on the coupling matrix, class vectors, and bias coefficient create a single segmentation vector of length n from the pixel vectors wherein each entry in the segmentation vector identifies one of the k class vectors, output the single segmentation vector; and operate the physical system based on the single segmentation vector.

A system for controlling a physical system via segmentation of an image includes a controller. The controller may be configured to receive an image of n pixels from a first sensor, and an annotation of the image from a second sensor, form a coupling matrix, k class vectors each of length n, and a bias coefficient based on the image and the annotation, generate n pixel vectors each of length n based on the coupling matrix, class vectors, and bias coefficient create a single segmentation vector of length n from the pixel vectors wherein each entry in the segmentation vector identifies one of the k class vectors, output the single segmentation vector; and operate the physical system based on the single segmentation vector.

Techniques for automatically determining, on a pixel by pixel basis, whether imagery includes ground images or is obscured by cloud cover. The techniques include training a Neural Network, making an initial determination of cloud or ground by using the Neural Network, and performing a max-flow, min-cut operation on the image to determine whether each pixel is a cloud or ground imagery.

Techniques for automatically determining, on a pixel by pixel basis, whether imagery includes ground images or is obscured by cloud cover. The techniques include training a Neural Network, making an initial determination of cloud or ground by using the Neural Network, and performing a max-flow, min-cut operation on the image to determine whether each pixel is a cloud or ground imagery.

Systems and methods for generating a probabilistic tree of vessels are provided. An input medical image of vessels of a patient is received. Anatomical landmarks are identified in the input medical image. A centerline of the vessels in the input medical image is determined based on the anatomical landmarks. A probabilistic tree of the vessels is generated based on a probability of fit of the anatomical landmarks and the centerline of the vessels. The probabilistic tree of the vessels is output.

A system comprises an encoder configured to compress and encode data for a three-dimensional mesh using a video encoding technique. To compress the three-dimensional mesh, the encoder determines sub-meshes and for each sub-mesh: texture patches and geometry patches. Also the encoder determines patch connectivity information and patch texture coordinates for the texture patches and geometry patches. The texture patches and geometry patches are packed into video image frames and encoded using a video codec. Additionally, the encoder determines boundary stitching information for the sub-meshes. A decoder receives a bit stream as generated by the encoder and reconstructs the three-dimensional mesh.