Registers – Coded record sensors – Particular sensor structure
Reexamination Certificate
2001-03-05
2004-02-03
Le, Thien M. (Department: 2876)
Registers
Coded record sensors
Particular sensor structure
C235S462250
Reexamination Certificate
active
06685095
ABSTRACT:
BACKGROUND OF THE INVENTION
Digital imaging technology continues to improve and find widespread acceptance in both consumer and industrial applications. Digital imaging sensors are now commonplace in video movie cameras, security cameras, video teleconference cameras, machine vision cameras and, more recently, hand-held bar code readers. As each application matures, the need for intelligent image processing techniques grows. To date, the large data volume attendant to transmitting a digital image from one location to another could only be accomplished if the two locations were connected by a wired means. Machine vision and imaging-based automatic identification applications required significant computing power to be effective and correspondingly require too much electricity to be useful in portable applications. The trend now in both consumer and industrial markets is toward the use of portable wireless imaging that incorporates automatic identification technology.
Historically, the automatic identification industry has relied on laser technology as the means for reading bar codes. Laser scanners generate a coherent light beam that is oriented by the operator to traverse the horizontal length of the bar code. The reflected intensity of the laser beam is used to extract the width information from the bars and spaces that are encountered. Laser scanners are effective in reading linear bar codes such as the U.P.C. code (found in retail point-of-sale applications), Code 39, Interleaved 2 of 5, or the like. Information stored in these linear (1D) bar codes is used to represent a short message or an index number related to a separate data file located in a central computer.
Imaging-based scanners use a solid-state image sensor such as a Charge Coupled Device (CCD) or a Complimentary Metal Oxide Semiconductor (CMOS) imager to convert an image scene into a collection of electronic signals. The image signals are processed so that any machine-readable character or bar code found in the field of view can be located in the electronic representation of the image and subsequently interpreted. The ability of image-based readers to capture an electronic image of a two-dimensional area for later processing makes them well suited for decoding all forms of machine-readable data at any orientation.
There are a number of advantages realized by using stacked-bar or matrix-type 2D bar codes. Due to the large capacity of 2D codes, an entire data record can be stored in the symbol. This means that instead of referencing a separate central computer data file upon reading the symbol, related information such as unit price, shipping destination, production history or any other user data can be extracted from the symbol itself. 2D bar codes are more compact and take up less label area than 1D codes while storing far more data.
All bar codes contain a number of common components that allow a reader to recognize and decode the symbol correctly. The code reader must be able to locate the code in a field of view, identify the type of bar code, determine the dimensions of the code, and then correctly decode the symbol in the presence of errors.
Linear bar codes and stacked linear bar codes possess a “start bar” pattern and a “stop bar” pattern that serve to identify both the type of bar code and the boundaries of the information. Matrix-type bar codes possess a “finder pattern” that serves the same purpose. Matrix code finder patterns are found either on the perimeter of the code or can be part of the internal structure of the code. Finder patterns typically incorporate additional information that allows the reader to determine code orientation.
Some 2D matrix codes can take on a number of allowed sizes or information densities. These types of codes must include easily detectable information that allows the reader to determine the bar code element size: the minimum height and width of a black or white area or “cell” in the code. Matrix codes typically possess a physical symmetry between the external size and the size of an individual cell. It is possible to determine the number of rows and columns of the matrix by knowing only the length of one side and the size of a single cell. For example, if an object within an image is found to be 100,000 pixels in height and the minimum distance between dark to light transitions is 7,962 pixels, the matrix height in elements can be calculated by dividing 100,000 by 7,962=13 elements high. For codes where only one physical size and information density is allowed, the number of rows and columns are known quantities. Although 2D bar codes are more compact than 1D codes, special care must be taken to ensure that the data stored in the code can be properly extracted. 1D codes provide “information redundancy” in the vertical direction. The taller the 1D codes, the greater the likelihood that a scan line will find and traverse an undamaged portion of the code thereby allowing a successful decode. 2D codes have built-in error detection and “error correction” data to allow the decoder to successfully decode a symbol even if part of the code is damaged or missing.
There are currently a wide variety of 2D codes that are in general use. Each code has a unique way of combining the three basic elements described above. Three of the most commonly used 2D codes include Data Matrix, PDF417, and MaxiCode.
Data Matrix is a matrix-type of 2D bar code that comes in a number of different array sizes and is identifiable by a finder pattern that occupies the perimeter of the optical code. The bottom and left edges of the code are solid black bars, forming an L-shaped pattern. The top and right edges of the code are made up of alternating black and white cells, allowing the reader to determine the number of rows and columns present in the matrix. The Data Matrix standard (ref) defines different types and levels of error correction, the preferred of which is ECC200. ECC200 uses a Reed-Solomon error correction scheme to allow the user to detect and correct a number of damaged bytes. Although most Data Matrix codes have an equal number of rows and columns, the standard allows for rectangular codes where there are twice the number of columns as rows.
PDF417 is a stacked-bar type of 2D bar code. PDF417 codes can be produced at a number of different aspect ratios, but are typically rectangular in shape. The code is identified by a start pattern that occupies the entire left edge of the symbol and a stop pattern occupying the entire right edge of the symbol. Data is stored in rows, with each row encoding the information in one of three schemes. Adjacent rows use different schemes, so the reader can correctly determine which row is being scanned. The code is also divided horizontally into segments. The first and last segment of every row contains Row Indicator data. The Row Indicator data always includes the current row number, and also includes one of the total number of rows in the symbol, the total number of columns in the symbol, or the security level of the symbol. Thus, the first segment of every third row encodes the total number of rows in the symbol, so the decoder can quickly determine how many rows it must detect. This information is also stored in the last segment of the row. PDF417 symbols employ varying levels of Reed-Solomon error correction coding to allow error detection and correction if part of the symbol is damaged or missing.
MaxiCode is a matrix-type code developed by UPS for parcel tracking. MaxiCode symbols have a distinctive ‘bulls-eye’ finder pattern located at the centre of the symbol. The code elements are hexagonal in shape and are placed on a hexagonal grid 30 elements wide by 33 elements high. The code supports only one size, and one information density, and is approximately 1.12 inches by 1.05 inches. MaxiCode symbols also employ Reed-Solomon error correction encoding to allow errors to be detected and corrected. In a MaxiCode symbol, data can be organized into a primary message and a secondary message. The primary message consists of 50% error control bits to ens
Priddy Dennis G.
Roustaei Alex
Xia Wenji
Katten Muchin Zavis & Rosenman
Le Thien M.
Symagery Microsystems Inc.
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