A global and local binary pattern image crack segmentation method based on robot vision comprises the following steps: enhancing a contrast of an acquired original image to obtain an enhanced map; using an improved local binary pattern detection algorithm to process the enhanced map and construct a saliency map; using the enhanced map and the saliency map to segment cracks and obtaining a global and local binary pattern automatic crack segmentation method; and evaluating performance of the obtained global and local binary pattern automatic crack segmentation method. The present application uses logarithmic transformation to enhance the contrast of a crack image, so that information of dark parts of the cracks is richer. Texture features of a rotation invariant local binary pattern are improved. Global information of four directions is integrated, and the law of universal gravitation and gray and roundness features are introduced to correct crack segmentation results, thereby improving segmentation accuracy. Crack regions can be segmented in the background of uneven illumination and complex textures. The method has good robustness and meets requirements of online detection.

Systems and methods for generating assessments based on construction site images are provided. For example, image data captured from a construction site using at least one image sensor may be obtained. Further, at least one electronic record associated with the construction site may be obtained. The image data and the at least one electronic record may be analyzed to generate at least one assessment related to the construction site. For example, the image data may be analyzed to identify at least one discrepancy between the at least one electronic record and the construction site, and the identified at least one discrepancy may be used in the generation of the at least one assessment.

A control device may obtain sensing data related to a paving material mat region laid by a screed assembly of a road paver. The control device may determine, based on the sensing data, a respective texture value and/or a respective height value associated with each portion of two or more portions of the paving material mat region. The control device may determine, based on the respective texture values and/or the respective height values of the paving material mat region, a finish value associated with the paving material mat region. The control device may cause, based on the finish value of the paving material mat region, one or more actions to be performed.

A processor of the inspection support device acquires an image obtained by imaging a structure to be inspected and detects damage to the structure on the basis of the acquired image. In a case where two or more types of damage (cracking B and linear free lime C.sub.2) to the structure are detected, the processor determines whether or not two or more types of damage are detected from the same or adjacent positions. In a case where determination is made that the cracking B and the linear free lime C.sub.2 are detected from the same or adjacent positions when the processor outputs the damage detection result (a damage image, a damage diagram, and the like), the processor preferentially outputs a damage detection result of the linear free lime C.sub.2 in accordance with a priority of a damage type (FIG. 16A and FIG. 16B).

Systems and methods for structure footprint detection from oblique imagery are disclosed, including a computer system configured to receive geo-referenced oblique images; analyze pixels of the images to: identify pixels representing a structure with walls; determine ground locations for the walls, geographic locations and orientations of pixels representing vertical edges of the walls, and relative lengths of the walls to produce horizontal line segments representing the base of the walls and having a relative length and an orientation, the horizontal line segment(s) determined from horizontal edge(s) extending a length between vertical edges above the bottoms of the vertical edges such that the horizontal edge is above the base of the structure; and assemble the horizontal line segments based on their relative lengths and orientations to form a footprint of the structure.

A method allows an estimator or other party to “Walk the Drawings.” An estimator can open one or more sets of drawings on a mobile device and walk those same electronic drawings as they actually walk or traverse the physical site itself. In other words, as the estimator physically moves across the construction site in the real world, their electronic icon (avatar) moves across the corresponding electronic drawings on their mobile device. Now the estimator can identify present and future such as features that need to be accessible being buried under asphalt. While walking the drawings, the estimator can label any challenges or features by simply clicking their avatar and it will post that geo-stamped location complete with corresponding notes and photos straight to the drawings for later review and analysis.

Even when a missing portion occurs in a solid data set on a columnar structure, an estimator for a deflection value and an accuracy of the deflection value are correctly estimated according to an extent of the missing portion and the like. A measurement accuracy estimation unit (15) is included that: calculates a deflection of a columnar structure and an extent of a missing portion, from a solid data set on the columnar structure; calculates an accuracy assessment indicator for the deflection that is acquirable when a plurality of missing portion patterns occur on a virtual basis, based on a plurality of solid data sets in each of which the calculated extent of the missing portion is smaller than a preset threshold value, the accuracy assessment indicator being calculated for each missing portion pattern; and calculates an accuracy of the deflection calculated from the solid data set, based on the calculated accuracy assessment indicator for each missing portion pattern, and based on the calculated extent of the missing portion in the solid data set.

A smart, human-centered technique that uses artificial intelligence and mixed reality to accelerate essential tasks of the inspectors such as defect measurement, condition assessment and data processing. For example, a bridge inspector can analyze some remote cracks located on a concrete pier, estimate their dimensional properties and perform condition assessment in real-time. The inspector can intervene in any step of the analysis/assessment and correct the operations of the artificial intelligence. Thereby, the inspector and the artificial intelligence will collaborate/communicate for improved visual inspection. This collective intelligence framework can be integrated in a mixed reality supported see-through headset or a hand-held device with the availability of sufficient hardware and sensors. Consequently, the methods reduce the inspection time and associated labor costs while ensuring reliable and objective infrastructure evaluation. Such methods offer contributions to infrastructure inspection, maintenance, management practice, and safety for the inspection personnel.

The present invention discloses a method and device for automatically drawing structural cracks and precisely measuring widths thereof. The method comprises a method for automatically drawing cracks and a method for calculating widths of these cracks based on a single-pixel skeleton and Zernike orthogonal moments, wherein the method for automatically drawing cracks is used to rapidly and precisely draw cracks in the surface of a structure, and the method for calculating widths of these cracks based on a single-pixel skeleton and Zernike orthogonal moments is used to calculate widths of macro-cracks and micro-cracks in an image in a real-time manner.

Provided is a damage information processing device, a damage information processing method, and a program that offer ease with which a user can recognize a point that has a chronologically unnatural difference. A damage information processing device (10) includes a processor (20) and is configured to process information about damage to a structure. The processor (20) is configured to acquire information about damage to a structure. The information includes first damage information about a state at one point in time and second damage information about a state at a later point in time than the first damage information. The processor (20) is configured to extract difference information concerning the difference between the first damage information and the second damage information. The processor (20) is configured to detect, by searching through the difference information, a first category point where only the first damage information is involved or where the first damage information is greater than the second damage information. The processor (20) is configured to output, to a display device, an alert indication in connection with at least one of the first damage information or the second damage information to give an indication of the first category point.