Uveye Ltd.

Amir Hever

Ohad Hever

Ilya Grinshpoun

Guy Engel

Itai Orr

Daniel Arzouan

Tomer Efi Daloomi

Noa Yedidia

Idan Cohen

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 single physical damage region.

Systems and methods for automated inspection of vehicles for body damage

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.

Generating interactive vehicle inspection interfaces using multi-model artificial intelligence and anchor-based spatial tracking

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.

Single pass automated vehicle inspection system and method

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Tenafly, NJ, United States of America

Amir Hever