초록 ▼

An identification system involves the labeling then tracking of grouped items such as logs, shipping containers, or packets of mail and reporting the current location of identified items during transport, processing, and storage. Machine-readable labels are provided, adapted for recognition and read

An identification system involves the labeling then tracking of grouped items such as logs, shipping containers, or packets of mail and reporting the current location of identified items during transport, processing, and storage. Machine-readable labels are provided, adapted for recognition and reading from within a cluttered scene. These labels have bordering indicia－used for locating purposes－distinguishable from inner informative indicia. Bordering indicia include either a series of small substantially similar marks like filled or hollow ovals, or one circle, or part of a circle, or a sequence of locating symbols or characters. Informative indicia include dots, bars, rings, or regional text characters. Multiple coding methods and spatial (e.g. Latin Square) replication of indicia are used to minimize errors. A machine-vision image decoder comprises a high-resolution camera adapted for field use and a remote image processing computer to analyze the image and make reports listing or showing items within the image as identified by labels.

대표청구항 ▼

A method of identifying each of a plurality of items at a site, comprising the steps of: labelling each of said items with a unique machine-readable label, each of said labels being different from each other of said labels, said label carrying a data matrix data field readable by machine vision read

A method of identifying each of a plurality of items at a site, comprising the steps of: labelling each of said items with a unique machine-readable label, each of said labels being different from each other of said labels, said label carrying a data matrix data field readable by machine vision reading equipment, said data matrix data field containing information-carrying indicia, the data field of each label being disposed in a machine-readable border, and an area of the field of view able to be read by said machine vision reading equipment containing a plurality of said labels, recording at least one image of the area of the field of view able to be read by said machine vision reading equipment, converting the image into a computer-compatible form, applying machine vision algorithms to detect the presence and position of each distinct data field within the image, and decoding only the information-carrying indicia in each data field located within said machine-readable borders to identify each item.