Abstract: A method for preprocessing sensor data applicable to sensor fusion for one or more sensors mounted on a vehicle is presented. The method comprises obtaining sensor data relating to common obstacles between the vision sensors and a lidar sensor, calculating range and azimuth values for the common obstacles from the lidar sensor data, and calculating range and azimuth values for the common obstacles from the vision sensor data. Then the method correlates the lidar sensor data pertaining to the common obstacles with the vision sensors pixels, formulates translations between the range values of the common obstacles and the one or more sensor tilt parameters, and performs recursive least squares to estimate an estimated sensor tilt for the vision sensors that can reduce range errors in the vision sensors.

Abstract: A system and method predicts pitting corrosion growth using imaging technology. In an embodiment, a first module preprocesses images to locate seed points, and a second module models a corrosion life cycle of the seed points. In another embodiment, the seed points are identified with defined confidence levels, and the rate of change of features in corrosion images is analyzed to identify dominant life-cycle phases of corrosion and defining corrosion impact factor for corrosion quantification.

Abstract: A system and a method to detect a label are described herein.

Abstract: Multi-resolution Signal Decomposition (MSD) levels for wavelet decomposition are determined automatically in real time. At each level of decomposition, local high frequency variations are eliminated or processed, while gradual patterns present in process control data are considered for further levels of decomposition. These wavelet coefficients are the approximate coefficients, are used for determining the suitable level of MSD. This invention utilizes signal-characterizing properties of these approximate coefficients for identifying suitable MSD levels. In one embodiment, an entropy measure is used and in the other embodiment, fractal dimension is used.

Abstract: A system and a method to extract dominant color information using fusion of color space data may include Red, Green, Blue (RGB) color space data and may include (H), Saturation (S), and Intensity Value (V) color space data. Red, Green and Blue color space histograms may be computed and maximum count values of each color space may be obtained, which may help finding ‘shine’ information in the object. Normalized HSV color space may be fused with Normalized RGB color space for dominant color determination. The dominant color decision conditions involved in the fusion process may change based on a ‘shine’ flag.