초록 ▼

A method and apparatus employs a production system-like rule based routine to process signals, such as reflectance signals produced from machine-readable symbols (e.g., bar code symbols). Relevant features data is extracted from each peak or valley in the signal, such as width, height, and relative

A method and apparatus employs a production system-like rule based routine to process signals, such as reflectance signals produced from machine-readable symbols (e.g., bar code symbols). Relevant features data is extracted from each peak or valley in the signal, such as width, height, and relative size. The routine then uses the extracted data for each peak and valley with a set of rules to refine the reflectance signals. Under one or more iterations, the routine selects and resolves conflicting rules and applies resulting rules to process the signal. The processed signal can then be more readily decoded. The routine preferably processes a reflectance signal in portions, such as on a codeword-by-codeword basis. Under an alternative embodiment, a fuzzy inference engine provides sets of values for height, width and relative size. Therefrom rules are applied to determine a size of each peak and valley in the signal.

대표청구항 ▼

[ What is claimed is:] [1.] In a symbol reading apparatus capable of storing a reflectance signal produced from a data collection symbol, the stored reflectance signal having a plurality of lobes representing peaks and valleys in the signal, a method of processing and decoding the reflectance signal

[ What is claimed is:] [1.] In a symbol reading apparatus capable of storing a reflectance signal produced from a data collection symbol, the stored reflectance signal having a plurality of lobes representing peaks and valleys in the signal, a method of processing and decoding the reflectance signal comprising:selecting at least a set of lobes from the plurality of lobes, the set of lobes corresponding to a portion of the reflectance signal;determining at least a first measurement with respect to at least some of the lobes in the set of lobes;comparing the first measurement of the first set of lobes to at least one membership function to produce a set of values for each lobe corresponding to the first measurement, wherein the membership function provides greater than two possible values for each lobe and wherein the set of values includes at least two confidence values for at least some of the lobes;applying at least one rule to the set of values and refining the portion of the reflectance signal based on the rule; anddecoding the portion of the reflectance signal.