Abstract: A joint approach of out-of-range detection and fault detection for power plant monitoring. The method initially determines whether a sensor is an independent sensor or a dependent sensor. If the sensor is an independent sensor, then an operating range is established for each independent sensor. A reading from each independent sensor is then compared with the operating range that has been established. If the reading is out-of-range, an alarm may be activated. If the reading is not out-of-range, then this reading is used to determine an expected operating range for each dependent sensor. A reading from each dependent sensor is then compared with the predicted operating range. Again, if the reading from the dependent sensor is out of the expected range, an alarm may be sounded.

Abstract: A system for generating a sensor model for use in sensor-based monitoring is provided. The system includes a segmenting module for segmenting a collection of sensor vectors into a plurality of bins comprising distinct sensor vectors. The system also includes a set-generating module for generating a set of statistically significant sensor vectors for each bin. The system further includes a consistency determination module for generating at least one consistent set of sensor vectors from the sets of statistically significant sensor vectors. Additionally, the system includes a model-generating module for generating a sensor model based upon the at least one consistent set.

Abstract: A method for object localization comprises defining an edge model for object localization, and searching an image for an object matching the edge model. Searching comprises defining a region of interest, including a portion of the object, sub-sampling the region of interest, and extracting an edge image comprising edges from the region of interest. Searching further comprises thinning at least one edge of the edge image, determining a distance map between the image and the edge image according to a distance transformation, and matching the edge model to the edge image within a search area defined according to the distance map.

Abstract: An intelligent camera system and method for recognizing license plates, in accordance with the invention, includes a camera adapted to independently capture a license plate image and recognize the license plate image. The camera includes a processor for managing image data and executing a license plate recognition program device. The license plate recognition program device includes a program for detecting orientation, position, illumination conditions and blurring of the image and accounting for the orientations, position, illumination conditions and blurring of the image to obtain a baseline image of the license plate. A segmenting program for segmenting characters depicted in the baseline image by employing a projection along a horizontal axis of the baseline image to identify positions of the characters. A statistical classifier is adapted for classifying the characters. The classifier recognizes the characters and returns a confidence score based on the probability of properly identifying each character.

Abstract: The present invention provides a method for detecting an object. The method includes capturing a binary image of the object, and determining a projection of the binary image to a first axis. The method further includes determining a difference between a profile of a target object to the first axis and the projection at a plurality of positions along the first axis, and detecting the object by determining if the difference between the profile and the projection is less than a threshold at one of the plurality of positions.

Abstract: A system and method for recognizing markers on, e.g., a PCB (printed circuit board). In one aspect, a system for recognizing a marker in an image comprises an image capture module (14) for extracting image features associated with an input image of a ROI (region of interest) captured through a lens 15, an image processor (16) comprising a first marker recognition processor (17) for recognizing a marker in the input image based on a normalized correlation and a second marker recognition processor (18) for recognizing a marker in the input image based on gray value histograms; a training module 19 for building template images and histograms that are used by the image processor (16) to detect a marker in the input image and a database (20) for indexing and storing trained template images and trained histograms.

Abstract: A method for segmenting and recognizing license plates, in accordance with the present invention includes capturing an image of a license plate and preprocessing the image to prepare the image for segmentation and recognition. Forward splitting regions of the license plate image into suspected characters regions, the suspected character regions are recognized in the license plate image and a confidence score is provided based on a probability of a correct match. If the suspected characters have a confidence score below a threshold value, backward merging is employed which merges adjacent suspected character regions. The backward merged suspected character regions in the license plate are recognized. If the backward merged suspected character regions have a confidence score below the threshold value, the backward merging and recognizing steps are repeated to improve the confidence score.

Abstract: A method for monitoring a slab filler, including grabbing a dispensing frame from a dispensing side of the slab filler, and grabbing a discharge frame from a discharge side of the slab filler. The method further includes classifying a plurality of cavities in the slab filler according to a correlation between the dispensing frame and at least one template, and classifying the plurality of cavities in the slab filler according to a correlation between the discharge frame and the template.