The techniques and device provided herein relate to receiving, via a processor, image data representative of a borehole of a well. The technique may include generating dequantized image data based on the image data, such that the dequantized image data filters one or more artifacts present in a Hough transformed version of the image data. One or more dip orientations (inclination and azimuth) associated with one or more formation dips present in the image data may be determined based on the dequantized image data. The technique may also include performing an a-contration validation algorithm for for the one or more formation dips to verify whether at least a formation dip having the or one of the possible dip orientation is present at a predetermined measured depth in the image data..

An example image feature extraction system comprises an encoder neural network having a first set of layers and a decoder neural network having a second set of layers and a third set of layers. The encoder neural network receives an input image, processes the input image through the first set of layers, and computes an encoded feature map based on the input image. The decoder neural network receives the encoded feature map, processes the encoded feature map through the second set of layers to compute a keypoint score map, and processes the encoded feature map through at least a portion of the third set of layers to compute a feature description map.

An example image feature extraction system comprises an encoder neural network having a first set of layers and a decoder neural network having a second set of layers and a third set of layers. The encoder neural network receives an input image, processes the input image through the first set of layers, and computes an encoded feature map based on the input image. The decoder neural network receives the encoded feature map, processes the encoded feature map through the second set of layers to compute a keypoint score map, and processes the encoded feature map through at least a portion of the third set of layers to compute a feature description map.

A method comprises generating a map comprising day-time features and night-time features, wherein the position of night-time features relative to the day-time features is determined by at least one image captured during twilight. The invention also relates to a corresponding processing unit configured to execute such a method.

A method comprises generating a map comprising day-time features and night-time features, wherein the position of night-time features relative to the day-time features is determined by at least one image captured during twilight. The invention also relates to a corresponding processing unit configured to execute such a method.

An image matching technique locates feature points in a template image such as a logo and then does the same in a test image. Feature points of a template image are determined under various transformations and used to determine a set of composite feature points for each template image. The composite feature points are used to determine if the template image is present in a test image.

The disclosure provides systems and methods for detecting, characterizing, and predicting moving traffic obstacles. The systems and methods are suitable for densely populated areas in resource-constrained regions. With the characterizations and predictions of moving traffic obstacles, a variety of benefits can accrue to individuals and devices that use traffic information.

A system and method for the measurement of distances related to an object depicted in an image. One aspect including delivery of supplemental materials for fenestration and for constructing insulating materials for fenestration. A digital image containing a primary object dimension and a reference object dimension in substantially the same plane undergoes digital image processing to provide improved measurement capability. Information regarding a primary object is provided to an automated measurement process, design and manufacturing system to provide customized parts to end users. A digital image is obtained having an observable constraint dimension to which a customized part is to conform wherein the digital image contains a reference object having a reference dimension and a constraint dimension is calculated from the digital image based on a reference dimension. The custom part is designed and manufactured based on the calculated constraint dimension.

Systems and methods for property feature detection and extraction using digital images. The image sources could include aerial imagery, satellite imagery, ground-based imagery, imagery taken from unmanned aerial vehicles (UAVs), mobile device imagery, etc. The detected geometric property features could include tree canopy, pools and other bodies of water, concrete flatwork, landscaping classifications (gravel, grass, concrete, asphalt, etc.), trampolines, property structural features (structures, buildings, pergolas, gazebos, terraces, retaining walls, and fences), and sports courts. The system can automatically extract these features from images and can then project them into world coordinates relative to a known surface in world coordinates (e.g., from a digital terrain model).

Systems and methods for property feature detection and extraction using digital images. The image sources could include aerial imagery, satellite imagery, ground-based imagery, imagery taken from unmanned aerial vehicles (UAVs), mobile device imagery, etc. The detected geometric property features could include tree canopy, pools and other bodies of water, concrete flatwork, landscaping classifications (gravel, grass, concrete, asphalt, etc.), trampolines, property structural features (structures, buildings, pergolas, gazebos, terraces, retaining walls, and fences), and sports courts. The system can automatically extract these features from images and can then project them into world coordinates relative to a known surface in world coordinates (e.g., from a digital terrain model).