Abstract: System and method for a computer vision technique for contactless measurement of vehicle toe are disclosed herein. The method includes capturing with a stereo camera an image containing a vehicle's wheel, segmenting the image, determining a suitable circular component of the wheel and computing the angle of the wheel relative to the camera and, subsequently, to the body of the vehicle. The method includes repeating the process for a plurality of wheels and computing the toe angle of the vehicle based on the obtained results.

Abstract: A computerized system for calibrating vehicle part measurements utilizes tire-based scale calibration with image processing and geometric compensation capabilities. The system automatically determines estimated tire size data from tire images using consensus-based algorithms, extracts actual tire specifications through optical character recognition, and calculates scale calibration data for converting pixel measurements to physical units. Geometric distortion detection and compensation handle angular misalignments between camera and tire planes. Real-time continuous calibration adapts to changing conditions during vehicle inspection operations. The calibration data integrates with defect detection and severity classification systems to enable accurate physical measurements of vehicle components and defects, providing calibration accuracy within 2% across varying operating conditions while accommodating diverse tire types and operational scenarios.

Abstract: There is provided a system for generating instructions for a generative model to present vehicle damage assessment. The system includes image sensors positioned at different heights and angles to capture vehicle images, a communication element for receiving images and accessing a stored model, and a processor connected to endpoint devices via a network. The processor generates instructional inputs combining damage severity classifications with vehicle images, sends these to the generative model, and obtains natural language elements for structural damage reconstitution. The system creates interactive presentations with populated template fields and classification selection elements displayed on endpoint devices. When users select different damage severity classifications in real-time, the system automatically generates new instructional inputs, obtains updated natural language elements from the generative model, and dynamically updates the presentation by replacing template fields.

Abstract: A system for inline measurement of gap width and flush depth of adjacent surfaces of a vehicle continuously moving longitudinally relative to the system comprises at least one laser source, at least one image sensor, and a processor configured to perform measurements within a predetermined cycle time. The processor controls the laser profiler to project laser beams onto vehicle surfaces, acquires optical images of reflected beams from the image sensor, and matches gap profiles from stored one-dimensional profiles to identify gaps. The system performs gap width and flush depth measurements and outputs anomaly detection signals when measurements deviate from predetermined target values. The system includes bias correction capabilities using empirically determined values and CAD-based target values for specific vehicle models. Dynamic adjustments are made based on vehicle color, with laser brightness optimized for surface reflectivity.

Abstract: A computer-implemented method and system for validating vehicle damage detection utilizes symmetry-based analysis of opposing vehicle sides. The method comprises receiving images from opposing sides of a vehicle, detecting a damage region in one image, and computing deep learning feature vectors for the damage region and a corresponding region in the opposite image. These feature vectors represent learned visual patterns that discriminate between damage and normal vehicle features. A similarity measure is computed between the feature vectors, and the detected damage is validated based on this measure. The system includes sensors for image capture, processors, and memory storing instructions to execute the method. This approach leverages vehicle symmetry to reduce false positives, compensate for environmental variations, and improve damage detection accuracy. The method can adapt to asymmetric vehicle positioning and varying environmental conditions, providing robust performance in real-world scenarios.

Abstract: A method and system for estimating dimensions of vehicle exterior defects using multiple cameras arranged in a predefined configuration. The method comprises receiving images from multiple strategically positioned image sensors including side cameras parallel to a vehicle height axis, diagonal cameras at an inclined angle, and roof top cameras perpendicular to the height axis. An angle to detected defects is computed based on image sensor parameters. Different distance calculations are applied based on vehicle section location, with specialized formulas for windshield, back window, and roof components. Defect sizes are computed by determining multiple defect dimensions, with at least one dimension being adjusted by an angular correction factor derived from the relationship between camera angle and vehicle surface orientation.

Abstract: There is provided a method of automatically detecting that a target image is deepfake, comprising: receiving authentic images depicting a vehicle with actual damage, receiving the target image depicting potential damage to the vehicle, feeding the target image into a machine learning (ML) model, obtaining a candidate set of human-readable text describing the potential damage to the vehicle, feeding the authentic images into the ML model, obtaining from the ML model, a ground truth set of human-readable text describing the actual damage to the vehicle depicted in the authentic images, computing a similarity metric indicating a difference between the potential damage described in the candidate set of human-readable text and the actual damage described in the ground truth set of human-readable text, and in response to the difference being above a threshold or meeting a requirement indicating a significant difference, detecting that the target image is likely deepfake.

Abstract: There is provided a method of image processing for detection of damage on a vehicle, comprising: accessing time-spaced image sequences depicting a region of a vehicle, captured by image sensors positioned at different heights and/or angles relative to the vehicle, identifying candidate regions of damage in the time-spaced image sequences, performing multi-level redundancy validation by: executing spatial correlation between images captured by different images sensors at different heights and/or different angles, executing temporal correlation between consecutive images captured by each image sensor, and validating persistence of each candidate region of damage across a threshold number of consecutive frames, identifying redundancy in the candidate regions of damage corresponding to a common physical location of the vehicle denoting a single physical damage region based on the multi-level redundancy validation, and providing an indication of the common physical location of the vehicle corresponding to the sing

Abstract: A method and system for estimating dimensions of vehicle exterior defects using multiple cameras arranged in a predefined configuration. The method comprises receiving images from multiple strategically positioned image sensors including side cameras parallel to a vehicle height axis, diagonal cameras at an inclined angle, and roof top cameras perpendicular to the height axis. An angle to detected defects is computed based on image sensor parameters. Different distance calculations are applied based on vehicle section location, with specialized formulas for windshield, back window, and roof components. Defect sizes are computed by determining multiple defect dimensions, with at least one dimension being adjusted by an angular correction factor derived from the relationship between camera angle and vehicle surface orientation.

Abstract: There is provided a method of image processing for detection of damage on a vehicle, comprising: accessing time-spaced image sequences depicting a region of a vehicle, captured by image sensors positioned at different heights and/or angles relative to the vehicle, identifying candidate regions of damage in the time-spaced image sequences, performing multi-level redundancy validation by: executing spatial correlation between images captured by different images sensors at different heights and/or different angles, executing temporal correlation between consecutive images captured by each image sensor, and validating persistence of each candidate region of damage across a threshold number of consecutive frames, identifying redundancy in the candidate regions of damage corresponding to a common physical location of the vehicle denoting a single physical damage region based on the multi-level redundancy validation, and providing an indication of the common physical location of the vehicle corresponding to the sing

Abstract: A system and method for generating an interactive user interface for inspection visualization. The system includes multiple imaging devices positioned along a inspection passage and at least one processor that executes instructions to: obtain multiple sets of images of vehicle surface segments captured during relative movement between the vehicle and imaging devices; stitch the images into a dataset record mapping vehicle parts and surface anomalies; transform the image data into a moving visual media object using a first generative AI model; compute a mapping record between segmented vehicle parts and target frame areas; and transform the mapping record and visual media object into an interactive interface using a second generative AI model. The interface displays user-selectable markers synchronized with media playback, indicating anomaly locations from multiple viewing angles, and performs data retrieval and display actions based on user selection of anomalies.

Abstract: A method of estimating dimensions of vehicle's exterior defects based on reference dimensions comprising analyzing one or more images captured by one or more image sensors deployed to depict a vehicle to identify one or more reference feature relating to the vehicle, obtaining real-world size of the reference feature(s), computing a pixel to real-world size ratio for the image sensor(s) based on the real-world size of the reference feature(s) and a size in pixels of the reference feature(s) in the image(s), analyzing one or more images captured by the image sensor(s) to identify one or more defects in an exterior of the vehicle, computing a size in pixels of one or more dimensions of each defect; and computing a real-world size of the dimension(s) based on the size in pixels of the respective dimension and the pixel to real-world size ratio.

Abstract: There is provided a computerized system comprising a processing unit and associated memory configured to obtain a three-dimensional dataset informative of at least part of a tread of a tire, and determine, using the three-dimensional dataset, data informative of tread depth of the tire.

Abstract: A method of estimating dimensions of vehicle's exterior defects based on reference dimensions comprising analyzing one or more images captured by one or more image sensors deployed to depict a vehicle to identify one or more reference feature relating to the vehicle, obtaining real-world size of the reference feature(s), computing a pixel to real-world size ratio for the image sensor(s) based on the real-world size of the reference feature(s) and a size in pixels of the reference feature(s) in the image(s), analyzing one or more images captured by the image sensor(s) to identify one or more defects in an exterior of the vehicle, computing a size in pixels of one or more dimensions of each defect; and computing a real-world size of the dimension(s) based on the size in pixels of the respective dimension and the pixel to real-world size ratio.

Abstract: There is provided a computer implemented method of image processing for detection of damage on a vehicle, comprising: accessing a plurality of time-spaced image sequences depicting a region of a vehicle, captured by a plurality of image sensors positioned at a plurality of different views, identifying a plurality of candidate regions of damage in the plurality of time-spaced image sequences, performing a spatiotemporal correlation between the plurality of time-spaced image sequences, identifying redundancy in the plurality of candidate regions of damage corresponding to a common physical location of the vehicle denoting a single physical damage region, and providing an indication of the common physical location of the vehicle corresponding to the single physical damage region.

Abstract: Systems and methods for onboard auto-inspection of vehicles using reflective surfaces. The system comprises at least one imaging device mounted on the vehicle, capturing reflections of the vehicle's exterior from strategically positioned reflective surfaces. The captured imaging data is processed by one or more processing circuitries to detect and analyse defects or anomalies on the vehicle's exterior surface. The invention also describes a support system consisting of a scaffold with mounted reflective surfaces, easily integrable into existing infrastructure. The system employs advanced image analysis techniques to accurately detect and localize defects, generating a detailed defect map. The invention further encompasses a complete kit, including the onboard auto-inspection system and the support system, providing a comprehensive solution for vehicle inspection and maintenance.

Abstract: A vehicle inspection system that images and assesses an automobile or truck during a single passage through an inspection area. Undercarriage, tire, and body imaging assemblies activate at coordinated times to optimally capture photos detailing the vehicle underbody, wheel, and profile views. The system improves imaging precision through targeted illumination and sensor arrays tailored to respective inspection zones. A computational core synchronizes aggregate sensor output to amalgamate a comprehensive perspective of the vehicle with minimized throughput timing. Automated analysis then identifies any defects, wear, or damage across imaging clusters. The system facilitates expedited assessment to categorize large vehicle pool conditions via an integrated mechanics-free apparatus requiring only conventional operator access.

Abstract: A system configured for verification of imaged target detection performs the following: (a) receive information indicative of at least two images of object(s). This information comprises candidate target detection region(s), indicative of possible detection of a target associated with the object(s). Images have at least partial overlap. The candidate region(s) appears at least partially in the overlap area. The images are associated with different relative positions of capturing imaging device(s) and of an imaged portion of the object(s). (b) process the information to determine whether the candidate region(s) meets a detection repetition criterion, the criterion indicative of repetition of candidate region(s) in locations of the images that are associated with a same location on a data representation of the object(s). (c) if the criterion is met, classify the candidate region(s) as verified target detection region(s). This facilitates output of an indication of the verified region(s).

Abstract: There are provided a system and a method of automatic tire inspection, the method comprising: obtaining at least one image capturing a wheel of a vehicle; segmenting the at least one image into image segments including a tire image segment corresponding to a tire of the wheel; straightening the tire image segment from a curved shape to a straight shape, giving rise to a straight tire segment; identifying text marked on the tire from the straight tire segment, comprising: detecting locations of a plurality of text portions on the straight tire segment, and recognizing text content for each of the text portions; and analyzing the recognized text content based on one or more predefined rules indicative of association between text content of different text portions at given relative locations, giving rise to a text analysis result indicative of condition of the tire.

Abstract: There is provided a computerized system comprising a processing unit and associated memory configured to obtain a three-dimensional dataset informative of at least part of a tread of a tire, and determine, using the three-dimensional dataset, data informative of tread depth of the tire.