Abstract: The present invention therefore provides a system and method of object detection that employs both global object detection and local object detection. In particular, the present invention applies global object detection techniques to detect global objects, and then applies local object detection techniques on select portions of detected global objects to detect local objects.

Abstract: A video-based fire detection system receives video data comprised of a plurality of individual frames, and determines based on the video data the ability of the system to detect the presence of fire. The system includes a video recognition system connectable to receive the video data and to calculate one or more background features associated with the video data. Based on the calculated background features, the video recognitions system assesses the ability of the video-based fire detection system to detect the presence of fire. The system includes one or more outputs operably connectable to communicate the results of the assessment made by the video recognitions system.

Abstract: A video-based object recognition system and method provides selective, local enhancement of image data for improved object-based recognition. A frame of video data is analyzed to detect objects to receive further analysis, these local portions of the frame being referred to as a region of interest (ROI). A video quality metric (VQM) value is calculated locally for each ROI to assess the quality of the ROI. Based on the VQM value calculated with respect to the ROI, a particular video quality enhancement (VQE) function is selected and applied to the ROI to cure deficiencies in the quality of the ROI. Based on the enhanced ROI, objects within the defined region can be accurately identified.

Abstract: An exemplary security device includes a controller that determines whether a security credential for an individual corresponds to an authorized credential. The controller also determines whether an acquired image of the individual corresponds to a reference image that is associated with the authorized credential. The controller determines if a correspondence between the acquired image and the reference image satisfies a selected criterion when the security credential corresponds to the authorized credential. The controller updates the reference image responsive to the selected criterion being satisfied. The controller updates the reference image by including the acquired image into the reference image and weighting the acquired image higher than other image information previously incorporated into the reference image.

Abstract: A video recognition system detects the presence of fire based on video data provided by one or more video detectors. The video recognition system divides each individual frame of video data into a plurality of frame elements and calculates with respect to each frame element a structural feature that the algorithm uses to identify a core region of potential fire. The video recognition system defines a region surrounding the core region and calculates with respect to each frame element within the surrounding region a temporal feature. Based on the calculated temporal feature, the video recognition system associates a representative temporal value with the core region. Based on the structural and temporal features associated with the core region, video recognition system determines whether the video data indicates the presence of fire.

Abstract: A system and method for performing automated defect detection by utilizing data from prior inspections is disclosed. The system and method may include providing a image capture device for capturing and transmitting at least one current image of an object and providing a database for storing at least one prior image from prior inspections. The system and method may further include registering the at least one current image with the at least one prior image, comparing the registered at least one current image with the at least one prior image to determine a transformation therebetween and updating the database with the at least one current image.

Abstract: A computer program product and method for performing automated defect detection of blades within an engine is disclosed. The method may include providing a storage medium for storing data and programs used in processing video images, providing a processing unit for processing images, receiving from a borescope an initial set of images of a plurality of members inside of a device, and using the processing unit to apply Robust Principal Component Analysis to decompose the initial set of images into a first series of low rank component images and a second series of sparse component images, wherein there are at least two images in the initial series.

Abstract: A system and method for performing automated defect detection of blades within an engine is disclosed. The system and method may include an image capture device capable of capturing and transmitting images of a plurality of blades of an engine, creating a normal blade model of an undamaged one of the plurality of blades and determining defects within the plurality of blades by utilizing the normal blade model.

Abstract: A system and method for improving human-machine interface while performing automated defect detection is disclosed. The system and method may include an image capture device for capturing and transmitting data of an object, performing automated analysis of the data and reviewing results of the automated analysis by a human inspector and providing feedback. The system and method may further include refining the automated analysis of the data based upon the feedback of the human inspector.

Abstract: A system and method for performing automated defect detection using multiple image capture devices is disclosed. The system and method may include providing a plurality of image capture devices, the plurality of image capture devices capturing and transmitting a plurality of images of an object. The system and method may further include determining a feature correspondence between the plurality of images of the plurality of image capture devices, creating mosaiced images of the plurality of images if the feature correspondence is found or known and performing at least of an automated analysis and a manual inspection on the mosaiced images to find any defects in the object.

Abstract: A computer program product and method for performing position control on device members that have been identified as defective. The method may include providing a storage medium that stores data and programs used in processing images and a processing unit that processes the images, receiving, by the processing unit from an image capture device coupled to the processing unit, a set of images of a plurality of members inside of a device, detecting, by the processing unit, a defect in a first member of the plurality of members, and providing instructions to move the first member to an inspection position in the device. The device may be an engine and the members may be blades within the engine.

Abstract: A video enhancement system provides automatic enhancement to video data that includes the presence of obscurations. The system provides near-field enhancement of the video data by detecting the presence of near-field obscurations such as snowflakes/raindrops and determining whether the detected obscurations are located over background pixels or foreground objects. The detected obscuration pixels are filled-in depending on whether they are located over the background or foreground to create an enhanced image. The system may also provide local/global adaptive contrast enhancement to enhance video in the presence of far-field obscurations.

Abstract: A closed-loop system employs video analytic outputs in a feedback loop to control the operation of a video-based fire detection system. In particular, video data captured by a video detector is analyzed by a video analytic system to generate outputs identifying regions indicative of fire. These outputs are employed as feedback in a closed-loop control system to orient the camera such that field of the view of the camera is modified to improve the ability of the video analytic system to verify or confirm the presence of fire within a region identified as indicative of fire. In addition, video analytic system may generate outputs identifying the delivery location of a fire suppressant. These outputs are employed as feedback in a closed-loop control system to orient the delivery of suppressant to extinguish the fire.

Abstract: A video-based object recognition system and method provides selective, local enhancement of image data for improved object-based recognition. A frame of video data is analyzed to detect objects to receive further analysis, these local portions of the frame being referred to as a region of interest (ROI). A video quality metric (VQM) value is calculated locally for each ROI to assess the quality of the ROI. Based on the VQM value calculated with respect to the ROI, a particular video quality enhancement (VQE) function is selected and applied to the ROI to cure deficiencies in the quality of the ROI. Based on the enhanced ROI, objects within the defined region can be accurately identified.

Abstract: A video recognition system detects the presence of fire based on video data provided by one or more video detectors, but suppresses the triggering of an alarm in situations based on the selection of acceptable regions and application of rules associated with each acceptable region. A user defines acceptable regions within the field of view of the video detector and associates with each acceptable region a rule. During processing of video data associated with the field of view, video metrics are calculated and analyzed to detect the presence of fire (e.g., flame or smoke). Prior to triggering an alarm, regions identified as indicative of fire are compared with the user-defined acceptable regions. If there is overlap between the two regions, the rule associated with the acceptable region is applied to determine whether the alarm should be suppressed or triggered.

Abstract: A video recognition system detects the presence of fire based on video data provided by one or more video detectors. The video recognition system divides each individual frame of video data into a plurality of frame elements and calculates with respect to each frame element a structural feature that the algorithm uses to identify a core region of potential fire. The video recognition system defines a region surrounding the core region and calculates with respect to each frame element within the surrounding region a temporal feature. Based on the calculated temporal feature, the video recognition system associates a representative temporal value with the core region. Based on the structural and temporal features associated with the core region, video recognition system determines whether the video data indicates the presence of fire.

Abstract: A video recognition system detects the presence of fire based on video data provided by one or more video detectors. The video recognition system is operable to calculate a first flicker feature with respect to a first set of frame data and a second flicker feature with respect to a second set of frame data. The video recognition system combines the first flicker feature and the second flicker feature to generate an accumulated flicker feature. The video recognition system defines, based on the accumulated flicker feature, a flicker mask that represents a dynamic region of the fire. Based on the defined flicker mask, the video recognition system determines whether the video data indicates the presence of fire.

Abstract: A video-based fire detection system receives video data comprised of a plurality of individual frames, and determines based on the video data the ability of the system to detect the presence of fire. The system includes a video recognition system connectable to receive the video data and to calculate one or more background features associated with the video data. Based on the calculated background features, the video recognitions system assesses the ability of the video-based fire detection system to detect the presence of fire. The system includes one or more outputs operably connectable to communicate the results of the assessment made by the video recognitions system.

Abstract: A method for multiple image restoration includes receiving a plurality of images corrupted by noise, and initializing a reduced noise estimate of the plurality of images. The method further includes estimating a probability of distributions of noise around each pixel and the probability of the signal, estimating mutual information between noise on the plurality of images based on the probabilities of distributions of noise around each pixel and the joint distribution of noise, and updating each pixel within a search range to determine a restored image by reducing the mutual information between the noise on the plurality of images.

Abstract: A gradient-based image enhancement and restoration method and system which applies an orientation-isotropy adaptive filter to the gradients of high structured regions, and directly suppresses the gradients in the noise or texture regions. A new gradient field is obtained from which image reconstruction can progress using least mean squares. The method generally comprises: inputting image data; calculating image gradients; defining the gradients as having large or small coherence; filtering the large coherence gradients for edge enhancement; suppressing the small coherence gradients for noise reduction; assembling an enhanced gradient field from the filtered large coherence and suppressed small coherence gradients; and optimizing the assembled gradient field into a restored image.