Abstract: A method of dimensioning an object includes: controlling an image sensor of the dimensioning device to capture image data representing the object; controlling a rangefinder of the dimensioning device to determine an object depth relative to the image sensor; detecting, in the image data, image corners representing corners of the object; determining a ground line and one or more measuring points of the image data based on the detected image corners; determining one or more image dimensions of the object based on the ground line and the one or more measuring points; determining a correspondence ratio of an image distance to an actual distance represented by the image distance based on the object depth, the ground line, and the one or more measuring points; and determining one or more dimensions of the object based on the one or more image dimensions and the correspondence ratio.

Abstract: An improved optical code reading system and method that enhances the ability of a reader to locate a symbol within a field of view and enhances the error-correcting properties of the encoding scheme commonly used in 2D bar codes. The reader offsets the effects of damaged finder patterns and missing symbol perimeters and, thereafter, detects high-level symbol information such as the code type, symbol size, and the number of rows and columns in the symbol. The reader then identifies those missing portions of a damaged symbol and marks each missing data bit location with a predetermined indicator. A decoding algorithm then interprets the missing bit indicator as an error of known location (e.g., an “erasure”), thereby nearly doubling the error correcting strength of all bar codes employing the Reed-Solomon error correction scheme.

Abstract: An optical imaging device and method which utilizes global feature extraction and local feature extraction to locate, identify and decode optical codes found within a captured image is disclosed. A global feature extraction unit first processes low-resolution image data to locate regions of interest that potentially contain the code(s). If no regions of interest are identified by processing the low-resolution image data, the global feature extraction unit then processes higher-resolution image data to locate the regions of interest. Any regions of interest located by the global feature extraction unit are then transferred to a local feature extraction unit which identifies and decodes a code found within a region of interest. Both the global feature extraction unit and the local feature extraction unit can begin processing data representative of portions of the image being captured before all of the data representative of the complete image is transferred to the respective unit.

Abstract: An improved optical code reading system and method that enhances the ability of a reader to locate a symbol within a field of view and enhances the error-correcting properties of the encoding scheme commonly used in 2D bar codes. The reader offsets the effects of damaged finder patterns and missing symbol perimeters and, thereafter, detects high-level symbol information such as the code type, symbol size, and the number of rows and columns in the symbol. The reader then identifies those missing portions of a damaged symbol and marks each missing data bit location with a predetermined indicator. A decoding algorithm then interprets the missing bit indicator as an error of known location (e.g., an “erasure”), thereby nearly doubling the error correcting strength of all bar codes employing the Reed-Solomon error correction scheme.