Abstract: A system and method for achieving constant magnification of a scanned three-dimensional item without the use of special optics or other specialized hardware. The system includes the dynamic computation of a camera parameter-dependent factor and applying that factor in real-time to the sampled signal resulting from the scan of the item.

Abstract: Systems and method for determining, based on a gray scale image, focus of an imaging system. A method of this invention includes the steps of: a) acquiring a gray scale image of a test target, b) binarizing the acquired gray scale image, c) analyzing the binarized acquired image, d) adjusting focus of acquisition optics of the imaging system, and e) repeating steps a) through d) until a substantially maximum number of line pairs of a number of groups of line pairs of the test target is obtained, wherein each group from the number of groups of line pairs has a predetermined spatial frequency.

Abstract: A system and method for collecting relatively high resolution amplitude data with a conventional sensing device from a signal source that is sampled at a relatively low characteristic scan resolution, and then generating relatively high scan resolution, relatively low resolution amplitude data through real-time application of up-sampling and quantization algorithms. The resulting relatively high scan resolution, relatively low resolution amplitude data closely approximate the image quality resulting from a sensing device operating at a much higher scan resolution, using a conventional data collection system. The invention relates generally to systems that collect the high resolution amplitude data that must be converted to low resolution amplitude data in order to maximize throughput rates.

Abstract: The present invention is directed to an object recognition system. The system includes a database having stored therein a trained reference vector. The trained reference vector includes a finite string of weighted reference feature elements optimized using a genetic algorithm which uses a dynamic length chromosome. The trained reference vector is optimized relative to a fitness function. The fitness function is an information based function. The trained reference vector corresponds to a known object or class of objects. A sensor is disposed in a surveilled region and configured to generate sensor data. The sensor data corresponds to objects disposed in the surveilled region. A recognition module is coupled to the sensor and the at least one database. The recognition module is configured to generate data object vectors from the sensor data. Each data object vector corresponds to one object.

Abstract: Systems and method for determining, based on a gray scale image, focus of an imaging system. A method of this invention includes the steps of: a) acquiring a gray scale image of a test target, b) binarizing the acquired gray scale image, c) analyzing the binarized acquired image, d) adjusting focus of acquisition optics of the imaging system, and e) repeating steps a) through d) until a substantially maximum number of line pairs of a number of groups of line pairs of the test target is obtained, wherein each group from the number of groups of line pairs has a predetermined spatial frequency.

Abstract: Methods for object recognition and systems that implement the methods. In one embodiment, the method of this invention for processing and identifying images includes two steps. In the first step, object profile characteristics are obtained. In the second step, object profile characteristics are utilized to determine object type and orientation. A system that implements the method of this invention is also disclosed.