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Thread: Image Processing and Barcodes

  1. #1
    Join Date
    May 2009
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    529

    Image Processing and Barcodes

    Hi friends,
    I am totally new for the field of the image processing and the barcodes. I have searched on the wen but I was not getting any appropriate information about it. So I thought that there would be someone over there, who might be interested in helping me.!! So please provide an information about the Image Processing and Barcodes. Hope that you guys will reply me soon.

  2. #2
    Join Date
    May 2008
    Posts
    390

    Re: Image Processing and Barcodes

    The documents are scanned for image processing or storage are often captured at 8 bits per pixel. They are called grayscale images in that 256 levels of gray are able to be represented in the image. The ability to represent shades of gray is required to faithfully capture photographs and graphics, but is not normally needed for text. Therefore, the scanned images are often binarized. This process involves selecting a threshold value and then changing all pixel values below it in black and all pixel values above the threshold to white. This compresses the image by only requiring 1 bit per pixel instead of 8 bits per pixel. For example, a 8.5 inch by 11 inch document scanned at 200 samples per inch, has a lower storage needs 3.6 megabytes to 450 kilobytes. Binarization also occurs when documents are faxed, the images are created, which are represented with 1 bit per pixel as well.

  3. #3
    Join Date
    May 2008
    Posts
    376

    Re: Image Processing and Barcodes

    Given an appropriate threshold, binarized images that contain text can normally be read either by the human eye or algorithms OCR. Indeed, some algorithms begin the process of optical character recognition OCR binarization of the image that the text is usually dark on a lighter background. However, if the barcodes are present in the binarized image, they can by altered enough by the binarization process to cause problems for a decoding algorithm.

  4. #4
    Join Date
    Aug 2006
    Posts
    209

    Re: Image Processing and Barcodes

    Density of the sample is the number of samples per unit area than the image is captured. densities typical sample used for the range of document processing 200 to 300 samples per inch (dots per inch or DPI). Fax transmission can vary from 100 to 400 DPI. In the decoding of bar codes, a more important parameter to consider is the samples per module, where module size is the size of the smallest element of the barcode. This distance is also called Dimension X. This parameter includes both the density of the sample image capturing device with the size of the bar code scanned. Volo, a bar code decoding software toolkit Omniplanar requires a minimum of 1.6 pixels per module for linear barcodes in an image to grayscale.
    Blessings to you

  5. #5
    Join Date
    Jul 2006
    Posts
    339

    Re: Image Processing and Barcodes

    The choice of symbology used to encode the data should also be carefully considered. Linear (or 1D) bar codes can be classified into two distinct groups: large / multiple codes and codes narrow width. In a wide / narrow code, each bar or space can be either narrow or wide. The range of reduction ratio, which gives the size ratio between the two widths, usually between 2 and 3. popular symbologies that use only 2 widths include code 39 and Interleaved 2 of 5. Multiple width codes have more than 2 choices for the widths of bars and spaces. popular symbologies which employ more than two widths include the UPC and Code 128, both of which allow a bar or a space of 1, 2, 3 or 4 modules.

  6. #6
    Join Date
    Aug 2006
    Posts
    181

    Re: Image Processing and Barcodes

    2D (or two dimensional) symbologies matrix codes are usually presence / absence. They use a grid of cells possible positions, and the presence or absence of a cell in a grid code data. Dimensional symbols have a data density much higher than the 1D data is stored in the two-dimensional symbol. In addition, they provide error correction to provide redundancy in case of certain data values cell can not be determined. When a 2D symbol is binarized enough samples per module (the size of a position on the grid), they tend to do better than linear codes that advanced information is not as critical: the position of the center of the cell that is more important.
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