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X9Utilities Qualify – OCR

X9Utilities Qualify

Qualify is used to run tiff validations against a folder (or folder of folders) using the same validations that are performed by our other tools such as X9Assist/X9Validator and the Tiff Tester. Qualify allows you to determine if your bitonal black-white TIFF images are compliant with the x9.100-181 exchange standards. Qualify can optionally repair those images that are determined to be non-compliant. An output CSV is created that contains a single line for each image processed, where the CSV identifies actions taken for each input image. When running with image repair, you must provide the output folder where the image repaired images will be written.

Qualify is designed to validate free-standing tiff images that are not embedded within an x9.37 file. By analyzing and repairing images prior to creating your x9.37 file, you can ensure that the images you ultimately insert into your image cash letters are x9.100-181 compliant, which greatly reduces the potential for returned items. Qualify is designed to process a small quantity of images as well as bulk processing of a very large number of items. Qualify is implemented as multi-threaded, which allows it to maximize processor (CPU) usage and minimize overall elapsed time. You can run tens of thousands of images through a single execution.

Qualify requires that you provide a configuration (-config: on the command line) that defines the rules that will be used to perform image validations. An example is -config:x9.37. By specifying the x9 configuration, you can ensure that you are applying the same tiff validation rules as you would be using with X9Assist. These rules will provide a variety of validations such as tiff tags, multi-strip, EOFB validation, and so forth. If you have specific image validation requirements to be applied, you can create your own tiffRules.xml and then incorporate those into a custom configuration using the Configuration Editor. Refer to that topic within this user guide as well as relevant help videos on our website.

Input Images from CSV or Folders

The input to qualify can be either an input CSV file which contains a list of the images to be processed, or it can be a folder that directly contains those images. When the input is a folder, the “-sf” switch can be optionally provided to indicate that the subfolders within the input folder should also be selected. When the input is a csv file, each line must contain two columns which are separated by a comma. The first columns must contain “image” and the second column must contain the image file name. Note that the file name should typically be enclosed within quote marks given that it may have embedded spaces.

Output CSV format

The output CSV identifies the input images that are processed along with actions that have been taken for each. The -weo switch can be used to limit the output csv to only those images that contain validation errors (accepted images will not be written). Columns are as follow:

  • Input image file name
  • Inspection message
  • Action message
  • Repaired image file name (written to the output image folder)
  • Image processing time in micro-seconds

X9Utilities OCR

OCR is an advanced tool that runs our E13B-OCR MICR line recognition facilities against front-side check images. It is used to automatically identify and extract E13B characters from the MICR band. Input can be an image folder or a CSV file that contains the fully qualifies file names of the images to be analyzed. Our E13B recognizer is 100% Java and applies advanced character isolation and recognition techniques to achieve the highest of recognition rates with performance that can reach 80-100 items per second. To use this function, the E13B-OCR feature must be enabled within your x9utilities license. Recognition results are written to an output CSV file that contains the MICR line, the parsed MICR fields, and the confidence level. Asterisks will appear as proxy for any characters that were identified but could not be read.

The OCR tool provides a command line (batch) interface to our E13B-OCR product. This gives you access to those facilities without having to write your own Java application program. Using our E13B-OCR product is more appropriate when you want to embed the recognition process directly in your own application.

Image conversion

The check images will ideally already be in TIFF format and x9.100-181 complaint, which means that they are suitable for x9.37 image exchange. If that is not the case, then our OCR function has the ability to resize and/or repair the images to ensure x9.100-181 compliance. These functions are turned off on a default basis. You must enable “-imageResizeEnabled” and “-imageRepairEnabled” if you want to use these image capabilities.

Although the images that are input to OCR are ideally in TIFF format, it will also automatically convert images to TIFF as needed from other formats such as PNG, JPG, GIF, or BMP. We nonetheless highly suggest that you avoid using our conversion facilities, since it adds substantially to runtime. It is important your image archive contains the check images as you are sending them to your processor or financial institution. For this reason, the best solution is to convert images elsewhere within your workflow, add them to your internal image archive, and then send the resulting TIFF images into the OCR recognition process.

E13B-Threading

E13B-OCR recognition can be a CPU intensive process. As part of optimization, recognition will be performed from a series of background threads that are run in parallel, with the intention to maximum performance and minimize overall run time.

The “-threads” parameter can be optionally provided to influence the number of background threads that will be used. For example, you can provide a switch value of “-threads:4″ to indicate that four (4) threads should be used for recognition processing. When this parameter is not provided, it will default to a reasonable setting based on the number of processors that are available on your system.

Input CSV Format

The input CSV is optional and can be used to provide the images to be analyzed. It is used as an alternative to providing the images within a folder (or folder of folders). The input CSV has only two columns:

  1. A row identifier which contains the text “image”, where the quotes are not needed.
  2. The fully qualified file name to be run through MICR line recognition.

Output CSV Format

OCR will create an output CSV that contains the E13B-OCR recognition results. The columns within this CSV are as follows:

  1. Line number.
  2. Image file name.
  3. Confidence level.
  4. Asterisk count with the recognized MICR line (these are digit errors).
  5. Image DPI.
  6. Image size in bytes.
  7. MICR Routing.
  8. MICR EPC.
  9. MICR OnUs.
  10. MICR AuxOnUs.
  11. MICR Amount.
  12. Entire MICR line as recognized.
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