Abstract: Methods, systems, and processor-readable media for pruning a training dictionary for use in detecting anomalous events from surveillance video. Training samples can be received, which correspond to normal events. A dictionary can then be constructed, which includes two or more classes of normal events from the training samples. Sparse codes are then generated for selected training samples with respect to the dictionary derived from the two or more classes of normal events. The size of the dictionary can then be reduced by removing redundant dictionary columns from the dictionary via analysis of the sparse codes. The dictionary is then optimized to yield a low reconstruction error and a high-interclass discriminability.

Abstract: Methods, systems and processor-readable media for enhancing performance of an automated license plate recognition system utilizing multiple results. Multiple images can be captured as a vehicle passes through an observation zone and each image can be processed utilizing an ALPR unit to obtain a plate code result and associated confidence values. Iterative processing of character level information across an OCR code followed by a higher level error checking based on learned context information can be performed. A string correlation approach can be employed to optimally align the OCR code from multiple images despite noise factors. The OCR confidence and state mask information can then be leveraged to select a character for an output plate code taking into account the ALPR error sources.

Abstract: Images with respect to an object at an ordering, payment, and delivery locations can be captured utilizing an image capturing system. Capture can be after detecting the presence of the object at each location utilizing an object presence sensor. The captured image can be processed to associate it with a signature and can also be processed in order to extract a small region of interest (e.g., license plate) and can be reduced to a unique signature. Signature can be stored into a database together with the corresponding order and images. Signatures can be matched. The order associated with the object matched by the system together with at least one of the images captured at the delivery point and the order point can be displayed at a user interface located at the payment/delivery point to ensure that the right order is delivered to the right customer associated with the object.

Abstract: Disclosed are methods and systems for monitoring and reporting road violations of vehicles sharing roads with responding emergency vehicles. According to an exemplary method video is captured from a forward and/or rear facing camera mounted to an emergency vehicle, and the video is processed to identify any vehicles in violation within a prescribed distance from the emergency vehicle. A license plate id of a vehicle determined to be in violation is identified and communicated to the appropriate authorities.

Abstract: The disclosure proposes the automatic use of the job or image content information of a print job. This information is used to automatically adjust the general printing procedure for a print engine. The job's image content information is analyzed in the context of the constraints of the print engine to determine an improved printing procedure, which may include cycle-up operation, process control cycles, or maintenance cycles for that particular print job.

Abstract: Methods and systems for reducing the required footprint of SNoW-based classifiers via optimization of classifier features. A compression technique involves two training cycles. The first cycle proceeds normally and the classifier weights from this cycle are used to rank the Successive Mean Quantization Transform (SMQT) features using several criteria. The top N (out of 512 features) are then chosen and the training cycle is repeated using only the top N features. It has been found that OCR accuracy is maintained using only 60 out of 512 features leading to an 88% reduction in RAM utilization at runtime. This coupled with a packing of the weights from doubles to single byte integers added a further 8× reduction in RAM footprint or a reduction of 68× over the baseline SNoW method.

Abstract: A method and system for recognizing a license plate character utilizing a machine learning classifier. A license plate image with respect to a vehicle can be captured by an image capturing unit and the license plate image can be segmented into license plate character images. The character image can be preprocessed to remove a local background variation in the image and to define a local feature utilizing a quantization transformation. A classification margin for each character image can be identified utilizing a set of machine learning classifiers each binary in nature, for the character image. Each binary classifier can be trained utilizing a character sample as a positive class and all other characters as well as non-character images as a negative class. The character type associated with the classifier with a largest classification margin can be determined and the OCR result can be declared.

Abstract: This disclosure provides methods and systems for troubleshooting charging and photoreceptor failure modes associated with a xerographic process. Specifically, according to an exemplary method the photoreceptor decay behavior, with and without the effects of depletion, are quantified and used to determine a performance state of one or more of the charging stations and the photoreceptor surface.

Abstract: A method determines a license plate layout configuration. The method includes generating at least one model representing a license plate layout configuration. The generating includes segmenting training images each defining a license plate to extract characters and logos from the training images. The segmenting includes calculating values corresponding to parameters of the license plate and features of the characters and logos. The segmenting includes estimating a likelihood function specified by the features using the values. The likelihood function measures deviations between an observed plate and the model. The method includes storing a layout structure and the distributions for each of the at least one model. The method includes receiving as input an observed image including a plate region. The method includes segmenting the plate region and determining a license plate layout configuration of the observed plate by comparing the segmented plate region to the at least one model.

Abstract: A system and method for automatically recognizing license plate information, the method comprising receiving an image of a license plate, and generating a plurality of image processing data sets, wherein each image processing data set of the plurality of image processing data sets is associated with a score of a plurality of scores by a scoring process comprising determining one or more image processing parameters, generating the image processing data set by processing the image using the one or more image processing parameters, generating the score based on the image processing data, and associating the image processing data set with the score.

Abstract: A method and system for achieving accurate segmentation of characters with respect to a license plate image within a tight bounding box image. A vehicle image can be captured by an image capturing unit and processed utilizing an ALPR unit. A vertical projection histogram can be calculated to produce an initial character boundary (cuts) and local statistical information can be employed to split a large cut and insert a missing character. The cut can be classified as a valid and/or a suspect character and the suspect character can be analyzed. The suspect character can be normalized and passed to an OCR module for decoding and generating a confidence quote with every conclusion. The non-character images can be rejected at the OCR level by enforcing a confidence threshold. An adjoining suspect narrow character can be combined and the OCR confidence of the combined character can be assessed.

Abstract: Methods, systems and processor-readable media for robust tilt adjustment and cropping of a license plate image. A vehicle image can be captured by an image-capturing unit and converted to a binary image utilizing a binarization approach. A long run within the binary image can then be removed and a morphological filtering can be applied to break an unwanted connection between characters due to a license plate frame and an image noise. A connected component (CC) within the image can be identified and screened based on a number of key metrics to remove a most likely candidate character connected component. A line-fit based iterative search process can then be performed for robust tilt removal and vertical cropping of the license plate image to obtain a tight bounding box on the license plate characters if sufficient candidate characters remain after the search process. Otherwise, the region of interest can be rejected.

Abstract: Embodiments relate to systems and methods for realtime occupancy detection of vehicles approaching a retail site for predictive ordering. A restaurant or other retail site can maintain access areas, such as a drive through lane or parking area, which vehicles can approach to order food or other items. A set of sensors can detect the vehicles, and estimate the number of occupants in those vehicles. Detection techniques can include face detection technology, seat detection technology, thermal imaging, or others. The number of occupants can be estimated and sent to a production management engine monitoring the site. That engine can responsively issue production instructions, such as a number and type of food items to prepare, and when. By integrating an operational model of the site, including projected order amounts and types, with the realtime occupant count, more accurate matching of food or other production to customer demand can be achieved.

Abstract: A method, system, and computer-usable tangible storage device for robustly cropping and accurately recognizing license plates to account for noise sources and interfering artifacts are disclosed. License plate images and sub-images can be tightly cropped utilizing an image-based classifier and gradient-based cropping. An image-based classifier can identify the location of valid characters within the image. Because of a number of noise sources, such as, for example, residual plate rotation and shear in the characters within the image, the image-based classifier performs a “rough” identification of the image boundaries. An additional processing step utilizing gradient-based cropping is performed to fine-tune the license plate image boundaries. Gradient-based cropping eliminates unwanted border artifacts that could substantially impact the segmentation and license plate character recognition results.

Abstract: A system and method by which, in photoreceptor devices that use non-contact charging, an impending failure of a photoreceptor can be accurately estimated based on a determined thickness of a charge transport layer in the photoreceptor. The systems and methods may include measuring current delivered to the photoreceptor charge transport layer, measuring voltage of the photoreceptor transport layer, determining a slope of the charge device, determining the thickness of the charge transport layer based on at least one of the measured current value, voltage value, or charge device slope, and determining a photoreceptor replacement interval based on the determined thickness.

Abstract: Method and system for enhancing performance of an automated license plate recognition system utilizing multiple results is disclosed herein. Multiple images can be captured as a vehicle passes through an observation zone and each image can be processed utilizing an ALPR unit to obtain a plate code result and associated confidence values. An iterative processing of character level information across an OCR code followed by a higher level error checking based on learned context information can be performed. A string correlation approach can be employed to optimally align the OCR code from multiple images despite noise factors. The OCR confidence and state mask information can then be leveraged to select a character for an output plate code taking into account the ALPR error sources. Such an approach leads to a more accurate result and increases the system yield.

Abstract: According to aspects of the embodiments, there is provided an apparatus comprising a cleaning unit with a blade holder that rotates about a pivot point, the cleaning blade is coupled to the blade holder and is positioned to chisel excess toner from a photoreceptor surface. Geometrical changes produce a blade having a slanted surface that reduces cyclic fatigue stress at the blade tip and reduces blade edge wear. The blade has a sharp leading side, a trailing side, and a working end comprising a slanted surface. When the slanted surface is formed at an angle between 93 degrees to 97 degrees stiffer tips is produced and wears resulting from blade and photoreceptor surface contact is reduced.

Abstract: A method and system for tracking a customer history data utilizing a combination of vehicle and facial information. A license plate image with respect to a customer vehicle can be captured and information with respect to the license plate obtained. The license plate information can be employed as an unique customer identifier with respect to customer history data, if the customer places an order (e.g., drive-through service). Facial images of the customer upon entry to a store and/or upon checkout can be captured and processed. The checkout image can be matched against a set of images in order to associate customer order information with customer history data identified from the license plate information for tracking an in-store order transaction.

Abstract: An embodiment generally relates to systems and methods for processing orders associated with an establishment. In particular, a customer can submit a remote order for goods offered by the establishment, along with an associated license plate number of a vehicle that is to pick up the order. An image capture device can capture images of a vehicle on the premises of the establishment, and provide the images to a processing module which use automatic license plate recognition (ALPR) techniques to determine license plate data of the vehicle. The processing module can further examine an order list to determine if the license plate data is associated with an order on the order list, and, if so, add the order to a priority queue.

Abstract: A method and system for recognizing a license plate character utilizing a machine learning classifier. A license plate image with respect to a vehicle can be captured by an image capturing unit and the license plate image can be segmented into license plate character images. The character image can be preprocessed to remove a local background variation in the image and to define a local feature utilizing a quantization transformation. A classification margin for each character image can be identified utilizing a set of machine learning classifiers each binary in nature, for the character image. Each binary classifier can be trained utilizing a character sample as a positive class and all other characters as well as non-character images as a negative class. The character type associated with the classifier with a largest classification margin can be determined and the OCR result can be declared.