Abstract: This invention provides a system and method for object detection and collision avoidance for objects and vehicles located behind the cab or front section of an elongated, and possibly tandem, vehicle. Through the use of narrow-baseline stereo vision that can be vertically oriented relative to the ground/road surface, the system and method can employ relatively inexpensive cameras, in a stereo relationship, on a low-profile mounting, to perform reliable detection with good range discrimination. The field of detection is sufficiently behind and aside the rear area to assure an adequate safety zone in most instances. Moreover, this system and method allows all equipment to be maintained on the cab of a tandem vehicle, rather than the interchangeable, and more-prone-to-damage cargo section and/or trailer. One or more cameras can be mounted on, or within, the mirror on each side, on aerodynamic fairings or other exposed locations of the vehicle.

Abstract: A stereo imaging based vision system to monitor the area on the two sides of either a door and control door motion according to the motion of 3D objects in the viewing area. The system calibrated to provide heights above the ground plane for any point in the field of view. Therefore, when any object enters the field of view, it generates interest points called “features”, the heights of which are measured relative to the ground plane. These points are then clustered in 3D space to provide “objects”. These objects are then tracked in multiple frames to provide “trajectories”. Such a system could then control the door motion (open, close, stall) based on the various pieces of information generated about the object.

Abstract: A stereo imaging based vision system is calibrated to provide heights above the ground plane for any point in the field of view. Therefore, when any object enters the field of view, it generates interest points called “features,” the heights of which are measured relative to the ground plane. These points are then clustered in 3D space to provide “objects.” These objects are then tracked in multiple frames to provide “trajectories.” Such a system could then control alarm signals or actuate gates or motion control devices, for example, based on the various pieces of information generated about the object.

Abstract: A method, computer program product, and machine vision system for monitoring an activity area proximate an actuated passageway for the occurrence of an object-related event. The activity area includes a first activity zone and at least a second activity zone. The first and the at least a second activity zones are essentially parallel to the activity area. The actuated passageway is actuatable with a control signal. The occurrence of an object-related event is detected within the activity area. If the object-related event occurs within the first activity zone, a first algorithm is executed to generate the control signal. If the object-related event occurs within the at least a second activity zone, a second algorithm is executed to generate the control signal.

Abstract: A stereo imaging based vision system and method provides enhanced portal security through stereoscopy. In particular, a system detects non-people objects within the chamber of a revolving door by acquiring two-dimensional (2D) images from different vantage points, and computing a filtered set of three-dimensional (3D) features of the door compartment by using both the acquired 2D images and model 2D images. Applying image processing techniques to the filtered 3D feature set, non-people objects can be detected.

Abstract: A two-dimensional (2-D) machine-vision safety-solution involving a method and apparatus for performing high-integrity, high efficiency machine vision. A known structured lighting texture pattern is projected upon a target area. A model image of the pattern on an empty target field is stored during an initial training step. The machine vision safety solution digitally interprets a camera image of the light reflected by the objects in the target area to detect and characterize a pattern in the image. The pattern characterization is then processed to determine if a distortion of the characterization factors is larger than a predetermined threshold, and results in an alarm condition.

Abstract: Disclosed is a method for determining the absence or presence of one or more instances of a predetermined pattern in an image, and for determining the location of each found instance within a multidimensional space. A model represents the pattern to be found, the model including a plurality of probes. Each probe represents a relative position at which a test is performed in an image at a given pose, each such test contributing evidence that the pattern exists at the pose. The method further includes a comparison of the model with a run-time image at each of a plurality of poses. A match score is computed at each pose to provide a match score surface. Then, the match score is compared with an accept threshold, and used to provide the location any instances of the pattern in the image.

Abstract: A method and system provides increased levels of security for a mantrap portal by continuously monitoring two zones of the mantrap; a primary zone and a secondary zone. A primary sensor determines that exactly one or zero people are present in the primary zone when requesting access into a secured area. A secondary sensor determines that exactly zero people are present in the secondary zone when access to the secured area is granted. The primary and secondary sensors in combination can detect piggyback events and tailgating events before granting access to a secured area. Further, the primary and secondary sensors in combination can detect the presence of unauthorized persons in a mantrap prior to granting access to the mantrap for exit from a secured area.

Abstract: Enhanced portal security is provided through stereoscopy, including a stereo door sensor for detecting and optionally preventing access violations, such as piggybacking and tailgating. A portal security system can include a 3D imaging system that generates a target volume from plural 2D images of a field of view about a portal; and a processor that detects and tracks people candidates moving through the target volume to detect a portal access event.

Abstract: A two-dimensional (2-D) machine-vision safety method and apparatus performs high-integrity, high efficiency machine vision. The system digitally filters a configurable number of time-sequenced camera images of a viewed area to create a filtered image. Objects within view in a training phase are detected and compared to objects detected in a runtime phase. Each new image is then compared to the previously created model and a pixel-oriented difference image is calculated. The difference image is then processed for segmentation features attributable to an intruder object. Alarm conditions are determined from threshold parameters related to location of the intruder objects. For segmentation results that exceed a predetermined threshold, an alarm condition is set. Setup parameters are automatically generated by analysis of distinctively marked physical boundaries in an image.

Abstract: A method of detecting a road lane in an electronically stored image. An image acquisition device acquires an image of a road lane environment and stores the image as an array of pixels. An edge detector generates a list of feature edges form the image. Lane marker edge pairs are filtered from the list of features according to a set of criteria. Lane marker edge pairs are sorted into lists corresponding to individual lane markers. Individual lane markers defining a left and right boundary of a road lane are geometrically identified. Three dimensional curves are fit along centers of mass of the sets of left and right lane markers to model a road lane boundary.

Abstract: A stereo imaging based vision system is calibrated to provide heights above the ground plane for any point in the field of view. Therefore, when any object enters the field of view, it generates interest points called “features,” the heights of which are measured relative to the ground plane. These points are then clustered in 3D space to provide “objects.” These objects are then tracked in multiple frames to provide “trajectories.” Such a system could then control alarm signals or actuate gates or motion control devices, for example, based on the various pieces of information generated about the object.

Abstract: A method and apparatus implementing dynamic thresholding techniques in processes that use image subtraction. The subtracted image is separated into a positive difference image using a positive image map and a negative difference image using a negative image map. A positive threshold map and a negative threshold map process a Gaussian filtered first image to generate respective positive and negative dynamic threshold images. The positive and negative threshold map mask out irrelevant areas and implement adaptive gain in pixel thresholds proportional to a difference or contrast between foreground or feature of interest and local background. Dynamic thresholding is a subtraction providing a subtracted positive image and a subtracted negative image. The subtracted positive and subtracted negative images are combined to provide a merged image which is binarized. Edge or Interface detection involves edge detection and true peak detection to find the edge peaks in a pre-image and post image.

Abstract: A stereo imaging based vision system to monitor the area on the two sides of either a door and control door motion according to the motion of 3D objects in the viewing area. The system calibrated to provide heights above the ground plane for any point in the field of view. Therefore, when any object enters the field of view, it generates interest points called “features”, the heights of which are measured relative to the ground plane. These points are then clustered in 3D space to provide “objects”. These objects are then tracked in multiple frames to provide “trajectories”. Such a system could then control the door motion (open, close, stall) based on the various pieces of information generated about the object.

Abstract: A three-dimensional (3-D) machine-vision involving a method and apparatus for performing segmentation of 3-D objects. Multiple stereo-related sets (left/right, top/left, top/right) of two-dimensional video pixel data are separately processed into sets of edges. Each stereo-related set is then pair-wise processed to convert pairs of sets of edge data into 3-D point data. Multiple sets of pair-wise 3-D data are then merged and used for obtaining 3-D features which are then clustered into discrete 3-D objects that can lie on any arbitrary plane.

Abstract: A three-dimensional (3-D) machine-vision obstacle detection solution involving a method and apparatus for performing high-integrity, high efficiency machine vision. The machine vision obstacle detection solution converts two-dimensional video pixel data into 3-D point data that is used for calculation of the closest distance from the vehicle to points on the 3-D objects, for any object within view of at least one imaging device configured to provide obstacle detection. The obstacle detection apparatus includes an image acquisition device arranged to view a monitored scene stereoscopically and pass the resulting multiple video output signals to a computer for further processing. The multiple video output signals are connected to the input of a video processor adapted to accept the video signals. Video images from each camera are then synchronously sampled, captured, and stored in a memory associated with a general purpose processor.

Abstract: A method of inspecting semiconductor die and lead frame assemblies uses rotation invariant/scale invariant processing methods of machine vision data. A training image is acquired and processed to form a training model. A runtime image is acquired and processed using rotation invariant/scale invariant tools to find a runtime instance of the trained model and produce x, y, theta and scale information. The runtime instance is aligned to the train time model, or vice versa, and then compared to the train time model. The features and edges from the runtime image are compared to features and edges of the training model to identify discrepancies as possible defects. The possible defects are further processed with a morphological filter and/or a blob filter to further refine images of the defects. Alternative implementations of the invention measure adhesive wet-out around semiconductor dies and provide measurements of die rotation.

Abstract: A two-dimensional (2-D) machine-vision safety-solution involving a method and apparatus for performing high-integrity, high efficiency machine vision. The machine vision safety solution digitally filters a configurable number of time-sequenced images of a viewed area to create a filtered image. A textured background is used as a static target and viewed under ambient light, or alternatively a texture is observed under IR light. An artificial texture can be created with a particularized pattern. Each new image is then compared to the previously created model and a pixel-oriented difference image is calculated. The difference image is then processed for segmentation features attributable to an intruder object. For segmentation results that exceed a predetermined threshold, an alarm condition is set.

Abstract: Machine vision methods for segmenting an image include the steps of generating a first image of the background of an object, generating a second image of the object and background, and subtracting the second image from the first image. The methods are characterized in that the second image is generated such that subtraction of it from the first image emphasizes the object with respect to the background.

Abstract: A three-dimensional (3-D) machine-vision safety-solution involving a method and apparatus for performing high-integrity, high efficiency machine vision. The machine vision safety solution converts two-dimensional video pixel data into 3-D point data that is used for characterization of specific 3-D objects, their orientation, and other object characteristics for any object, to provide a video safety “curtain.” A (3-D) machine-vision safety-solution apparatus includes an image acquisition device arranged to view a target scene stereoscopically and pass the resulting multiple video output signals to a computer for further processing. The multiple video output signals are connected to the input of a video processor adapted to accept the video signals. Video images from each camera are then synchronously sampled, captured, and stored in a memory associated with a general purpose processor.