Siemens Aktiengesellschaft

Inspekto A.m.v. Ltd.

Pointgrab Ltd.

Yonatan Hyatt

Harel Boren

Alexander Spivak

Ran Ginsburg

Joel Koenka

Dan Carmon

Benjamin Neeman

Jonathan Laserson

Itamar Roth

David Ungarish

Katherina Shefer

Sivan Mottes

Gil Zohav

Dagan Eshar

Michael Gotlieb

Zohar Kantor

Embodiments of the invention provide a system and method for a visual inspection process, in which images of objects on an inspection line are automatically grouped into clusters based on the appearance of the object in the images. The clustered images create a broad database of images that can be used as a reference for inspected items having different appearances, which ensures that all parts and appearances of an inspected object can be identified and inspected, thereby increasing the success of defect detection and substantially minimizing false detection of defects.

Optimizing a set-up stage in an automatic visual inspection process

Embodiments of the invention provide a system and method for integrating HDR images in video processing in a time efficient process. In one embodiment, a method for machine vision image processing includes obtaining a plurality of images of a scene, each image having a different exposure value. The images are captured by a camera having a specific dynamic range. Pixel values of the plurality of images are compared to the dynamic range of the camera to determine, based on the comparison, a minimal number of optimal images. This minimal number of optimal images is combined, to obtain an HDR image of the scene. The scene may include an object on an inspection line.

Use of an HDR image in a visual inspection process

A visual inspection data collection and analysis system comprising: a plurality of visual inspection appliances (VTA) configured to inspect and acquire visual inspection data relating to inspected items; and a data collection and analytics server (DCAS) configured to receive information comprising the visual inspection data from the multiple VIAs and to analyze the received information to form a big data analysis. The VIAs are adapted for detecting defects or gating or counting the inspected items without the involvement of the DCAS.

Centralized analytics of multiple visual inspection appliances

A method and system for automated visual inspection of an object include using different patterns of illumination, each pattern including constant frequency pulses of illumination. The pulses of each different pattern of illumination are temporally offset so as to enable obtaining images illuminated by one or another illumination pattern. The images are combined using different parts of the different images in which the most details of the object are available, to produce a full image of the object which is essentially glare-free. The use of constant frequency pulses enables obtaining different pattern illumination images, to enable creating a glare-free image of an object, while providing a flicker-free inspection environment for human workers.

System and method for imaging reflecting objects

An automatic inspection process for detecting visible defects on a manufactured item, the process including a set up mode in which images of same-type defect free items, but not images of same-type defected items, are obtained, and an inspection mode in which images of both same-type defect free items and same-type defected items, are obtained and defects are detected, where images of the same-type defect free items are analyzed and based on the analysis the process switches to the inspection mode.

System and method for set up of production line inspection

Embodiments of the invention provide automatic detection of same-type objects on an inspection line and automatically capture and/or display an image of the object once it is detected. Additionally, embodiments of the invention automatically provide the outline of an object to a user, enabling the user to either confirm or easily correct the outline. The confirmed or corrected outline is then automatically applied to all images of inspected items of the same-type, allowing optimization of inspection tasks such as defect detection, for all inspected items, based on a short, possibly a one-time, input, from the user.

Streamlining an automatic visual inspection process

Embodiments of the invention provide a machine learning based detection system, in which defects can be detected even if the system was not trained for these defects and even in items that were not used to train the system, thereby offering an inherently flexible detection system.

System and method for detecting defects on imaged items

An appliance and method for automated visual inspection of at least two items from different categories, on a production line, include automatically switching between an item profile of a first of the at least two items for inspection; and an item profile of a second of the at least two items for inspection, based on detection of the first item in an image of the production line.

System and method for visual production line inspection of different production items

A system for visual inspection, which includes a processor that receives a sensitivity level relating to an image of an item on an inspection line, the image being displayed on the user interface device, and calculates a minimal defect size visible in the image at the received sensitivity level. The calculated minimal defect size is then displayed on a user interface. This visual demonstration of minimal detectable size, which changes as the user changes sensitivity level, enables the user to easily obtain a desired minimal detectable defect size.

User interface device for autonomous machine vision inspection

An appliance for concurrent automated visual inspection of at least two items comprising: at least two inspection assemblies each comprising a camera assembly, wherein each one of the at least two items is inspected by one of the at least two Inspection assemblies; a controller in data communication with the at least two inspection assemblies, wherein the controller is a computing device, wherein the appliance is adapted to be automatically configured for inspecting the at least two items using the at least two inspection assemblies.

Multi-camera visual inspection appliance and method of use

A method and system for automated visual inspection, include receiving, from a camera imaging an inspection line, an image of the inspection line. The image includes an item on the inspection line personal or confidential image data. A processor produces from the image of the inspection line a reduced image, which does not include the personal or confidential image data, and inputs the reduced image to an inspection process.

System and method for automated visual inspection

The invention provides an automatic inspection process for detecting visible defects on a manufactured item. The process includes a set up mode in which images of same-type defect free items, but not images of same-type defected items, are obtained, and an inspection mode in which images of both same-type defect free items and same-type defected items, are obtained and defects are detected. Images of the same-type defect free items are analyzed and based on the analysis the process switches to the inspection mode.

An object is tracked in images of the space. A unique identification is assigned to the object and the uniquely identified object may then be located within the space based on the tracking of the object, without having to again uniquely identify the object.

Method and system for locating an occupant

A method and system for detecting occupancy in a space use computer vision techniques. In one embodiment an object is detected in an image of the space. If the object is detected in a first area of the image, a shape of the object is determined based on a first shape feature of the object and if the object is detected in a second area of the image, the shape of the object is determined based on a second shape feature of the object. The object may be determined to be an occupant based on the determined shape of the object.

Growing community of inventors

Tel Aviv, Israel

Yonatan Hyatt