Abstract: Techniques for using imaging information computed from examining a scanner signal are described. When one or more objects passes within a field of view of a scanner, scan patterns emerging from one or more scanner windows and reflected from the objects back into the scanner windows produce one or more scanner signals. The scanner signals are processed to obtain beam position and beam length information to improve the accuracy of bar code decoding and to compute imaging information for objects within the field of view of the scanner. The imaging information for the objects is compared with bar code information for the objects. The expected number, size and shapes of objects indicated by the bar code information is compared with the actual number, size and shapes of objects in order to determine if valid scans occurred or if missed, double or otherwise erroneous scans occurred.

Abstract: Techniques for using imaging information computed from examining a scanner signal are described. When one or more objects passes within a field of view of a scanner, scan patterns emerging from one or more scanner windows and reflected from the objects back into the scanner windows produce one or more scanner signals. The scanner signals are processed to obtain beam position and beam length information to improve the accuracy of bar code decoding and to compute imaging information for objects within the field of view of the scanner. The imaging information for the objects is compared with bar code information for the objects. The expected number, size and shapes of objects indicated by the bar code information is compared with the actual number, size and shapes of objects in order to determine if valid scans occurred or if missed, double or otherwise erroneous scans occurred.

Abstract: A produce texture data collecting apparatus and method which illuminates a produce item from different directions. The apparatus includes a first light for illuminating a produce item from a first direction, a second light for illuminating the produce item from a second direction, an image capture device for capturing an image of the produce item while the produce item is being illuminated by the first and second lights.

Abstract: Techniques for using a scan pattern to estimate imaging information for an object reflecting the scan pattern are described. As an object is brought within range of a scan window, a scan beam tracing out a scan pattern comprising a plurality of scan lines causes reflection of the scan beam back into the scan window to produce a scanner signal based on reflections of the scan beam. The time at which the scanner signal indicates the presence of an object is noted and this timing information is mapped to position information identifying the position of the scan beam. The timing and position information is used to estimate imaging information about the object, including position, size, shape and motion information.

Abstract: A method of combining spectral data with non-spectral data which uses a defined distance measure of likeness (DML) value and conditional probabilities. The method includes the steps of collecting the spectral and non-spectral data for the produce item, determining DML values between the spectral and the non-spectral data and reference produce data for a plurality of types of produce items, determining conditional probability densities for all of the types of produce items using the DML values, combining the conditional probability densities to form a combined conditional probability density, and determining probabilities for the types of produce items from the combined conditional probability density.

Abstract: An ambient light sensing apparatus and method for a produce data collector which minimize false triggering of produce data collection. The apparatus includes an image capture device which has a first receiving angle for incident light through an aperture in the produce data collector which is larger than a second receiving angle of a collector within the produce data collector which collects produce data.

Abstract: A produce recognition system and method which use a distance measure of likeness calculation to identify a produce item. The system includes a produce data collector, a library, and a computer. The produce data collector collects first data from the produce item. The library contains second data associated with classes of produce items. The computer reads the second data from a library, determines a distance measure of likeness value between the first data and each of the second data, determines third data and a corresponding class of produce items from the second data which produces a smallest distance measure of likeness value, and identifies the produce item to be within the corresponding class of produce items.

Abstract: Techniques for removing noise effects in processing a barcode signal. A photosignal produced by scanning a barcode is used to generate a digital first derivative signal. Positive and negative thresholds are generated based on the digital first derivative signal. Processing windows are defined for each region of the first derivative signal which exceeds a threshold. Each processing window is bounded by a window opening point at which the first derivative signal exceeds a threshold, and by a window closing point, which is the last crossing of the threshold by the first derivative signal before the first derivative signal makes a zero crossing. Each region is processed to locate a geometric center of the region. A logic transition is recognized for the geometric center of each region defined by a processing window.

Abstract: A produce data collector which includes a spectrometer which minimizes noise from scattered light and from wavelengths outside the operating range of the spectrometer. The produce data collector includes a light source for illuminating a produce item. The spectrometer obtains spectral information about the produce item in incoming reflected light from the produce item and includes a linear variable filter, a photodetector adjacent the linear variable filter, and an optical slit member above a primary surface of the linear variable filter which has a slit with a width sufficient to minimize scattering of the incoming light by interior surfaces of the linear variable filter. The produce data collector may additionally include a filter, such as an infrared filter.

Abstract: A produce recognition system and method which use an internal reference to calibrate a produce data collector. The produce data collector collects first data from an external reference, collects second and third data from an internal reference, and collects fourth data from a produce item. A computer determines a first calibration value from the first and second data and a second calibration value from the third data and applies the first and second calibration values to the fourth data to produce fifth data. The computer further obtains sixth data from reference produce data and compares the fifth and sixth data to identify the produce item.

Abstract: A produce recognition system and method which use an internal reference to calibrate a produce data collector. The produce data collector collects first data from an external reference, collects second and third data from an internal reference, and collects fourth data from a produce item. A computer determines a first calibration value from the first and second data and a second calibration value from the third data and applies the first and second calibration values to the fourth data to produce fifth data. The computer further obtains sixth data from reference produce data and compares the fifth and sixth data to identify the produce item.

Abstract: A method of recognizing produce items which uses checkout frequency as an a priori probability. The method includes the steps of collecting produce data from the produce item, determining DML values between the produce data and reference produce data for a plurality of types of produce items, determining conditional probability densities for all of the types of produce items using the DML values, combining the conditional probability densities together to form a combined conditional probability density, determining checkout frequencies for the produce types, determining probabilities for the types of produce items from the combined conditional probability density and the checkout frequencies, determining a number of candidate identifications from the probabilities, and identifying the produce item from the number candidate identifications.

Abstract: A produce data collector and produce recognition system which illuminates a produce item with substantially uniform light to enhance the accuracy of collected produce data and subsequent identification of the produce item as part of a transaction in a transaction establishment. The produce data collector includes a light source for illuminating the produce item with substantially uniform light during the transaction, a light separating element for splitting light collected from the produce item into a plurality of different light portions having different wavelengths, a detector for converting energy in the plurality of light portions into a plurality of electrical signals, and control circuitry which digitizes the plurality of electrical signals to produce a digital spectrum from the produce item which contains information to identify the produce item for the purpose of determining its unit price.

Abstract: A produce data collector which operates with less than uniform lighting. The produce data collector includes a light source for illuminating a produce item with light, collecting optics for collecting reflected light from the produce item including a Lambertian reflector, a light separating element which produces an image from collected light, and an image capture device which captures discrete wavelengths within the collected light.

Abstract: A produce data collector and produce recognition system which illuminates a produce item with substantially uniform light to enhance the accuracy of collected produce data and subsequent identification of the produce item as part of a transaction in a transaction establishment. The produce data collector includes a light source for illuminating the produce item with substantially uniform light during the transaction, a light separating element for splitting light collected from the produce item into a plurality of different light portions having different wavelengths, a detector for converting energy in the plurality of light portions into a plurality of electrical signals, and control circuitry which digitizes the plurality of electrical signals to produce a digital spectrum from the produce item which contains information to identify the produce item for the purpose of determining its unit price.

Abstract: A produce data collector and produce recognition system which illuminates a produce item with substantially uniform light to enhance the accuracy of collected produce data and subsequent identification of the produce item as part of a transaction in a transaction establishment. The produce data collector includes a light source for illuminating the produce item with substantially uniform light during the transaction, a light separating element for splitting light collected from the produce item into a plurality of different light portions having different wavelengths, a detector for converting energy in the plurality of light portions into a plurality of electrical signals, and control circuitry which digitizes the plurality of electrical signals to produce a digital spectrum from the produce item which contains information to identify the produce item for the purpose of determining its unit price.

Abstract: A produce data collector with minimal spectral distortion. The produce data collector includes a light pipe having entrance and exit ends through which a portion of light reflected from a produce item travels, and a spectrometer adjacent the exit end of the light pipe which splits the portion of light into a plurality of wavelengths and which produces signals associated with the wavelengths for identifying the produce item.